# Best Predictive Analytics Software for Small Business *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)* Products classified in the overall Predictive Analytics category are similar in many regards and help companies of all sizes solve their business problems. However, small business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Small Business Predictive Analytics to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Small Business Predictive Analytics category. In addition to qualifying for inclusion in the Predictive Analytics Software category, to qualify for inclusion in the Small Business Predictive Analytics Software category, a product must have at least 10 reviews left by a reviewer from a small business. ## Top Predictive Analytics Software at a Glance | # | Product | Rating | Best For | What Users Say | |---|---------|--------|----------|----------------| | 1 | [Tableau](https://www.g2.com/products/tableau/reviews) | 4.4/5.0 (3,675 reviews) | Visual data storytelling with drag-and-drop forecasting | "[Turning Complex Data into Actionable Insights](https://www.g2.com/survey_responses/tableau-review-13075232)" | | 2 | [Clari](https://www.g2.com/products/clari/reviews) | 4.6/5.0 (5,503 reviews) | AI-driven revenue forecasting inside Salesforce pipelines | "[Clari Platform Review from a RevOps Perspective](https://www.g2.com/survey_responses/clari-review-12400239)" | | 3 | [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) | 4.3/5.0 (774 reviews) | Enterprise ML model governance with low-code deployment | "[Effective Data Analysis with SAS Viya](https://www.g2.com/survey_responses/sas-viya-review-11872818)" | | 4 | [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) | 4.5/5.0 (1,144 reviews) | SQL-based ML modeling on petabyte-scale datasets | "[Easy-to-Use Cloud Tool with Shareable, Saved Queries](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)" | | 5 | [Adobe Analytics](https://www.g2.com/products/adobe-analytics/reviews) | 4.2/5.0 (1,173 reviews) | Cross-channel customer journey analytics with Adobe integration | "[Powerful, Detailed Insights with Customizable Dashboards in Adobe Analytics](https://www.g2.com/survey_responses/adobe-analytics-review-12644645)" | | 6 | [IBM Cognos Analytics](https://www.g2.com/products/ibm-cognos-analytics/reviews) | 4.1/5.0 (438 reviews) | Enterprise forecasting with governed data models | "[Powerful, Scalable Analytics with Interactive Dashboards and Strong Governance](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-12770018)" | | 7 | [Amazon QuickSight](https://www.g2.com/products/amazon-quicksight/reviews) | 4.3/5.0 (676 reviews) | AWS-native dashboards with ML-powered forecasting | "[Fast, Serverless BI with Seamless AWS Integration](https://www.g2.com/survey_responses/amazon-quicksight-review-11692248)" | | 8 | [IBM SPSS Statistics](https://www.g2.com/products/ibm-spss-statistics/reviews) | 4.2/5.0 (893 reviews) | Point-and-click statistical modeling for non-programmers | "[Efficient, Reliable Statistical Analysis with an Approachable UI in IBM SPSS Statistics](https://www.g2.com/survey_responses/ibm-spss-statistics-review-12829044)" | | 9 | [SAP Analytics Cloud](https://www.g2.com/products/sap-analytics-cloud/reviews) | 4.2/5.0 (750 reviews) | — | "[SAP Analytics Cloud Clean Dashboards and Powerful Real Time Analytics in One Place](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12817514)" | | 10 | [SAP HANA Cloud](https://www.g2.com/products/sap-hana-cloud-2025-10-01/reviews) | 4.3/5.0 (521 reviews) | Real-time predictive analytics on SAP transactional data | "[Efficient Transactions, But Time-Intensive Setup](https://www.g2.com/survey_responses/sap-hana-cloud-review-12983922)" | --- ## What Are the Most Common Questions About Predictive Analytics Software? *AI-generated · Last updated: May 26, 2026* ### Which Predictive Analytics platforms let non-technical analysts build models without writing code? Based on G2 reviews, several predictive analytics tools are consistently described as approachable for non-technical users because they rely on visual workflows, drag-and-drop interfaces, or low-code model building. According to verified users, SAS Viya stands out for letting teams analyze data, build models, and create dashboards without heavy coding, while still supporting code when needed. G2 reviewers mention Pecan as a way to run predictive models quickly without a dedicated data science team, and Alteryx is often praised for making data preparation and analytics easier for business users who are not coders. These themes point to tools that reduce technical barriers while still supporting practical predictive work. **Here are some of the top-rated products on G2:** - [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews/sas-viya-review-12717278) – supports no-code and code-based analytics with automated reporting and fast model work - [Pecan](https://www.g2.com/products/pecan/reviews/pecan-review-12160044) – helps teams run predictive models quickly without needing a full data science team - [Alteryx](https://www.g2.com/products/alteryx/reviews/alteryx-review-12847135) – enables non-coders to prep data, automate tasks, and produce KPI reporting ### Which Predictive Analytics platforms avoid predictions that fail spectacularly in live production environments? Based on G2 reviews, buyers tend to trust platforms that reviewers describe as reliable in production, easy to validate, and supported by strong deployment workflows. According to verified users, Pecan is frequently praised for getting predictive models live quickly and helping teams use them in sales, fraud, and demand planning use cases without a large data science function. G2 reviewers mention that it is not a black box to the same degree as some alternatives and that support teams help with setup and model improvement, which can reduce production risk. Reviews also suggest that platforms with clear monitoring, data organization, and repeatable workflows tend to inspire more confidence once predictions move into business operations. ### What Predictive Analytics most trusted by analytics leaders and data professionals based on verified reviews? Based on G2 reviews, Tableau appears most trusted by analytics leaders and data professionals in this review set because it has the strongest concentration of recent verified feedback and is repeatedly described as reliable for turning complex data into clear, actionable insights. According to verified users, Tableau helps analysts build dashboards quickly, connect multiple data sources, and support leadership reviews with interactive reporting. G2 reviewers mention its drag-and-drop workflow, strong visualization capabilities, and usefulness for spotting trends, tracking KPIs, and improving decision-making across teams. While users also note tradeoffs like pricing and learning curve, the recurring trust signal in these reviews comes from its widespread day-to-day use in analytics workflows. ### What Predictive Analytics with explainable results that business teams can trust and confidently act on? Based on G2 reviews, buyers looking for explainable predictive analytics often favor platforms that make model logic, signals, or statistical outputs easier to interpret for business teams. According to verified users, Pecan is valued because teams can analyze data, build predictive models, and review model behavior with support that helps business users understand results. G2 reviewers mention that GoodData.AI helps turn complex metrics into clearer dashboards and actionable insight, while IBM SPSS Statistics is repeatedly praised for making advanced statistical analysis approachable through structured outputs, tables, and charts. Across these reviews, trust tends to come from platforms that combine prediction with understandable presentation, not just raw model output. ### What most trusted Predictive Analytics by data teams and analysts based on verified user reviews? Based on G2 reviews, Tableau is the most trusted predictive analytics option in this dataset for data teams and analysts because reviewers repeatedly describe it as a dependable platform for analyzing large datasets, building dashboards, and sharing insights with both technical and non-technical stakeholders. According to verified users, Tableau shortens the time from raw data to decisions with drag-and-drop workflows, strong data connectivity, and interactive dashboards. G2 reviewers mention use cases ranging from forecasting and KPI tracking to supply chain analysis and executive reporting. The strongest trust signal here is not just positive sentiment, but the volume and consistency of recent reviews describing Tableau as part of daily analytics work. ### What Predictive Analytics platforms where models actually improve business decisions instead of sitting unused? Based on G2 reviews, the platforms that stand out are the ones reviewers say are tied directly to sales, operations, forecasting, or retention decisions rather than isolated experiments. According to verified users, Pecan helps teams prioritize leads, predict churn, forecast demand, and support next-purchase planning, which makes the outputs easier to operationalize. G2 reviewers mention SAS Viya as useful for large-scale analytics, dashboards, and machine learning in one environment, helping teams move from raw data to action more efficiently. Reviews also show that platforms gain adoption when they reduce manual work, fit existing workflows, and let business teams understand results without relying on a separate specialist team every time. ### Which Predictive Analytics tools require less data preparation and programming expertise than traditional approaches? Based on G2 reviews, several tools are described as reducing the amount of data preparation and coding typically associated with predictive analytics. According to verified users, Amazon Forecast helps teams generate forecasts without needing deep machine learning expertise, while Pecan is valued for letting SQL-capable or semi-technical users create predictive models without a full data science workflow. G2 reviewers mention Alteryx as especially helpful for cleaning, blending, and automating data preparation through a drag-and-drop interface. SAS Viya also appears in reviews as a low-code or no-code option for modeling and dashboarding. Overall, reviewers favor platforms that automate prep work, simplify model setup, and shorten the path from raw data to usable predictions. ### What highest rated Predictive Analytics for driving accurate and actionable business forecasting consistently? Based on G2 reviews, accurate and actionable business forecasting is most often associated with tools built for repeatable forecasting workflows and clear operational outputs. According to verified users, Nixtla is praised for fast forecasting, zero-shot forecasting across many series, and strong ease of use for sales, energy, and demand forecasting scenarios. G2 reviewers mention Amazon Forecast for reliable demand planning and inventory forecasting without requiring deep machine learning expertise. SAS Visual Forecasting is also highlighted for large-scale automated forecasting that provides a strong baseline. Across these reviews, the most valued forecasting platforms are those that save time, support faster decisions, and make forecasts practical enough to guide planning rather than stay theoretical. ### What is the best Predictive Analytics for teams turning raw data into accurate business forecasts without specialist PhDs? Based on G2 reviews, Pecan is the best fit for teams that want to turn raw data into usable business forecasts without needing specialist data science expertise. According to verified users, Pecan helps organizations build predictive models quickly through an interface that is approachable for SQL users and semi-technical teams, with strong support throughout setup and deployment. G2 reviewers mention use cases such as sales forecasting, customer lifetime value, churn prediction, lead prioritization, and demand planning. Reviews consistently describe faster time to value, easier onboarding, and practical business outputs. That combination makes it especially appealing for teams that want forecasting capability without building a full in-house modeling function. ### What top Predictive Analytics solutions predicting customer churn before valuable customers leave the business? Based on G2 reviews, churn prediction is most strongly associated with platforms that help teams identify at-risk users early enough to act. According to verified users, Pecan is repeatedly used for churn risk analysis, customer lifetime value, next-purchase prediction, and identifying high-value customers for more targeted outreach. G2 reviewers mention Amazon Forecast and Nixtla more often for demand and time-series forecasting, while Pecan stands out for customer-focused predictive use cases tied to retention and commercial action. Reviews suggest that churn tools are most valuable when they turn raw customer data into practical signals for sales, marketing, or customer teams, helping them focus on intervention before customers disengage. **Here are some of the top-rated products on G2:** - [Pecan](https://www.g2.com/products/pecan/reviews/pecan-review-11579534) – used for churn risk analysis and broader customer behavior prediction - [Amazon Forecast](https://www.g2.com/products/amazon-forecast/reviews/amazon-forecast-review-12255988) – supports planning with more reliable forecasts for resource and business decisions - [Nixtla](https://www.g2.com/products/nixtla/reviews/nixtla-review-11514059) – helps teams maintain high-quality forecasts with minimal model overhead ## G2 Grid® for Predictive Analytics Software ![G2 Grid® for Predictive Analytics Software plotting products by satisfaction and market presence](https://www.g2.com/categories/predictive-analytics/grids.png?focus%5B%5D=1213&focus%5B%5D=1327283&focus%5B%5D=20158&focus%5B%5D=3558&focus%5B%5D=612&focus%5B%5D=610&focus%5B%5D=87427&focus%5B%5D=35854) Highlighted products: Tableau, SAS Viya, Amazon QuickSight, Adobe Analytics, IBM Cognos Analytics, GoodData.AI, Amazon Forecast, and SAP Analytics Cloud. Underlying data: [Grid® JSON](https://www.g2.com/categories/predictive-analytics/grids.json?focus%5B%5D=tableau&focus%5B%5D=sas-sas-viya&focus%5B%5D=amazon-quicksight&focus%5B%5D=adobe-analytics&focus%5B%5D=ibm-cognos-analytics&focus%5B%5D=gooddata-ai&focus%5B%5D=amazon-forecast&focus%5B%5D=sap-analytics-cloud&segment=small-business) ## How Many Predictive Analytics Software Products Does G2 Track? **Total Products under this Category:** 299 ### Category Stats (Jul 2026) - **Average Rating**: 4.44/5 The average rating of products in this category, based on all submitted ratings - **Top Trending Product**: Logility Solutions (+0.68%) - Among all products in this category, Logility Solutions recorded the largest rating increase compared to last month *Last updated: July 25, 2026* ## How Does G2 Rank Predictive Analytics Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 31,700+ Authentic Reviews - 299+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. --- **Sponsored** ### KNIME KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice. [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=499&secure%5Bchosen_at%5D=2026-07-27T16%3A51%3A57Z&secure%5Bdisplayable_resource_id%5D=499&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=499&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=16291&secure%5Bresource_id%5D=499&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=llm_category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fpredictive-analytics%2Fsmall-business&secure%5Btoken%5D=4fad03cc552ff45c9065479599a4fec361f6b762a7367cadfabc560c1479ddf9&secure%5Burl%5D=https%3A%2F%2Fwww.knime.com%2Flp%2Fdemo%3Futm_medium%3D3rd-party%26utm_source%3DG2%26utm_campaign%3Dbrand%26utm_term%3Dpaid%26utm_content%3D&secure%5Burl_type%5D=custom_url) --- ## What Are the Top-Rated Predictive Analytics Software Products in 2026? ### 1. [Tableau](https://www.g2.com/products/tableau/reviews) Tableau is the world’s leading AI-powered analytics platform. Whether you are a business user or an analyst, Tableau turns trusted data into actionable insights. With our flexible, interoperable platform, you can: Turn data into action at scale with human and agent collaboration. Tableau Next delivers agentic AI for faster data-insight-action workflows. It surfaces insights, provides proactive recommendations, and helps you take action in the flow of work. Scale data-driven insights with complete operational confidence. Tableau Cloud enables fully managed analytics at scale. It accelerates your time to value and gives you access to the latest AI-powered innovations. Deploy visual, self-service analytics with unmatched control and flexibility. Tableau Server meets your organization's governance and security needs. It provides enterprise-grade, self-service analytics on-premise or in your private cloud. **Average Rating:** 4.4/5.0 **Total Reviews:** 3,675 **How Do G2 Users Rate Tableau?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **AI Text Summarization:** 8.0/10 (Category avg: 8.1/10) - **Algorithms:** 8.4/10 (Category avg: 8.5/10) - **AI Text Generation:** 8.0/10 (Category avg: 8.1/10) **Who Is the Company Behind Tableau?** - **Seller:** [Salesforce](https://www.g2.com/sellers/salesforce) - **Company Website:** https://www.salesforce.com/ - **Year Founded:** 1999 - **HQ Location:** San Francisco, CA - **Twitter:** @salesforce (579,511 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3185/ (83,223 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Business Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 41% Enterprise, 36% Mid-Market #### What Are Tableau's Pros and Cons? **Pros:** - Ease of Use (634 reviews) - Data Visualization (563 reviews) - Visualization (424 reviews) - Features (351 reviews) - Intuitive (317 reviews) **Cons:** - Learning Curve (275 reviews) - Learning Difficulty (240 reviews) - Expensive (225 reviews) - Slow Performance (155 reviews) - Difficulty (139 reviews) ### What Do G2 Reviewers Say About Tableau? *AI-generated summary from verified user reviews* **Pros:** - Users find Tableau's **ease of use** essential for creating interactive dashboards without heavy coding or complex setups. - Users value Tableau's **data visualization capabilities** , enabling the creation of interactive, clear dashboards that enhance decision-making. - Users love Tableau for its **powerful visualization capabilities** , enabling clear, interactive dashboards and real-time data insights. - Users value the **interactive dashboards** of Tableau, enhancing data visualization and simplifying complex reporting tasks seamlessly. - Users love Tableau's **intuitive interface** , making complex data visualization and dashboard creation easy and accessible. **Cons:** - Users find the **learning curve steep** , making it challenging to fully integrate Tableau with Salesforce and MS products. - Users face a **steep learning curve** with Tableau, making it challenging for new users to become proficient. - Users report that the **high licensing cost** of Tableau can be a significant barrier, especially for smaller teams. - Users report **slow performance** with large datasets, impacting their experience and efficiency in Tableau. - Users find Tableau's **onboarding and complexity** challenging, making it tougher to transition from simpler tools like MS products. #### What Are Recent G2 Reviews of Tableau? **"[Clear data means quick decisions.](https://www.g2.com/survey_responses/tableau-review-13124621)"** **Rating:** 4.5/5.0 stars *— Libia B.* [Read full review](https://www.g2.com/survey_responses/tableau-review-13124621) --- **"[Turning Complex Data into Actionable Insights](https://www.g2.com/survey_responses/tableau-review-13075232)"** **Rating:** 5.0/5.0 stars *— Murtuza L.* [Read full review](https://www.g2.com/survey_responses/tableau-review-13075232) --- #### What Are G2 Users Discussing About Tableau? - [How are business intelligence professionals using Tableau's latest visualization tools to interpret complex data sets?](https://www.g2.com/discussions/how-are-business-intelligence-professionals-using-tableau-s-latest-visualization-tools-to-interpret-complex-data-sets) - 2 comments - [What is Salesforce CRM Analytics (formerly Tableau CRM) used for?](https://www.g2.com/discussions/what-is-salesforce-crm-analytics-formerly-tableau-crm-used-for) - [Do I need Tableau Desktop if I have Tableau Server?](https://www.g2.com/discussions/tableau-do-i-need-tableau-desktop-if-i-have-tableau-server) - 2 comments - [Do I need Tableau Desktop if I have Tableau Server?](https://www.g2.com/discussions/do-i-need-tableau-desktop-if-i-have-tableau-server) - 2 comments - [What's New in Tableau Server?](https://www.g2.com/discussions/what-s-new-in-tableau-server) - 1 comment ### 2. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control. **Average Rating:** 4.3/5.0 **Total Reviews:** 774 **How Do G2 Users Rate SAS Viya?** - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 8.9/10) - **AI Text Summarization:** 6.7/10 (Category avg: 8.1/10) - **Algorithms:** 8.6/10 (Category avg: 8.5/10) - **AI Text Generation:** 6.3/10 (Category avg: 8.1/10) **Who Is the Company Behind SAS Viya?** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Company Website:** https://www.sas.com/ - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,863 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,638 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Student, Biostatistician - **Top Industries:** Pharmaceuticals, Banking - **Company Size:** 33% Enterprise, 33% Small-Business #### What Are SAS Viya's Pros and Cons? **Pros:** - Ease of Use (234 reviews) - Features (218 reviews) - Analytics (196 reviews) - Data Analysis (166 reviews) - Intuitive (145 reviews) **Cons:** - Learning Difficulty (151 reviews) - Learning Curve (144 reviews) - Complexity (143 reviews) - Difficult Learning (117 reviews) - Expensive (108 reviews) ### What Do G2 Reviewers Say About SAS Viya? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of SAS Viya, which simplifies data visualization and enhances decision-making efficiency. - Users value the **sophisticated analytical capabilities** of SAS Viya, enabling easy deployment and real-time decision-making. - Users appreciate the **advanced analytical methods** offered by SAS Viya, enhancing decision-making and logistical data analysis capabilities. - Users value the **end-to-end data lifecycle tooling** of SAS Viya, enhancing business insight and strategic decision-making. - Users love the **intuitive interface** of SAS Viya, making data analysis and model deployment effortless for all skill levels. **Cons:** - Users find SAS Viya to have a **learning difficulty** , making it challenging for non-technical individuals to navigate effectively. - Users find the **learning curve steep** , making it challenging for non-technical users to navigate SAS Viya effectively. - Users find the **visualization complexity** in SAS Viya challenging, particularly for non-technical users and beginners. - Users struggle with the **difficult learning curve** of SAS Viya, particularly for new and non-technical users. - Users find the **expensive pricing** of SAS Viya to be a significant barrier to entry for potential adoption. #### What Are Recent G2 Reviews of SAS Viya? **"[Effective Data Analysis with SAS Viya](https://www.g2.com/survey_responses/sas-viya-review-11872818)"** **Rating:** 4.5/5.0 stars *— Fungai J.* [Read full review](https://www.g2.com/survey_responses/sas-viya-review-11872818) --- **"[SAS Viya: Powerful AI & Data Analysis with Seamless Integrations](https://www.g2.com/survey_responses/sas-viya-review-11855145)"** **Rating:** 5.0/5.0 stars *— Verified User in Hospital & Health Care* [Read full review](https://www.g2.com/survey_responses/sas-viya-review-11855145) --- #### What Are G2 Users Discussing About SAS Viya? - [What is SAS Visual Data Mining and Machine Learning used for?](https://www.g2.com/discussions/what-is-sas-visual-data-mining-and-machine-learning-used-for) - 2 comments ### 3. [Amazon QuickSight](https://www.g2.com/products/amazon-quicksight/reviews) Amazon QuickSight is a cloud-based unified business intelligence (BI) service at hyperscale. With QuickSight, all users can meet varying analytic needs from the same source of truth through modern interactive dashboards, paginated reports, natural language queries and embedded analytics. With Amazon Q in QuickSight, business analysts and business users can use natural language to build, discover, and share meaningful insights in seconds, turning insights into impact faster. Over 100,000 customers use Amazon QuickSight. Learn more at https://quicksight.aws **Average Rating:** 4.3/5.0 **Total Reviews:** 676 **How Do G2 Users Rate Amazon QuickSight?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **AI Text Summarization:** 8.2/10 (Category avg: 8.1/10) - **Algorithms:** 8.1/10 (Category avg: 8.5/10) - **AI Text Generation:** 8.2/10 (Category avg: 8.1/10) **Who Is the Company Behind Amazon QuickSight?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,232,483 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (147,094 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Who Uses This:** Data Analyst, Software Engineer - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 40% Small-Business, 37% Mid-Market #### What Are Amazon QuickSight's Pros and Cons? **Pros:** - Integrations (69 reviews) - Ease of Use (62 reviews) - Easy Integrations (57 reviews) - Data Visualization (41 reviews) - Dashboard Management (39 reviews) **Cons:** - Limited Customization (62 reviews) - Learning Curve (36 reviews) - Limited Visualization (26 reviews) - Missing Features (20 reviews) - Poor Interface Design (20 reviews) ### What Do G2 Reviewers Say About Amazon QuickSight? *AI-generated summary from verified user reviews* **Pros:** - Users enjoy the **seamless integration with AWS services** , allowing for quick and effective dashboard creation. - Users find Amazon QuickSight to be **very user-friendly** , seamlessly integrating with AWS for a smooth experience. - Users appreciate the **easy integrations** of Amazon QuickSight, enhancing convenience with AWS and other data sources. - Users value the **interactive dashboards and data visualization tools** of Amazon QuickSight, enhancing real-time insights for their business. - Users admire the **interactive dashboard management** of Amazon QuickSight, enabling seamless data visualization and real-time insights. **Cons:** - Users find the **limited customization options** of Amazon QuickSight restricts the flexibility of their reporting needs. - Users find the **learning curve steep** , requiring additional AWS knowledge for effective use of QuickSight's features. - Users find the **visualization options limited** , making it tough to achieve desired dashboard customizations and interactivity. - Users find **missing features** in Amazon QuickSight, particularly lacking customization and advanced analytics compared to competitors. - Users find the **poor interface design** of Amazon QuickSight detracts from usability and hinders deeper data analysis. #### What Are Recent G2 Reviews of Amazon QuickSight? **"[Fast, Serverless BI with Seamless AWS Integration](https://www.g2.com/survey_responses/amazon-quicksight-review-11692248)"** **Rating:** 4.5/5.0 stars *— Jawher S.* [Read full review](https://www.g2.com/survey_responses/amazon-quicksight-review-11692248) --- **"[Streamlined Reporting with Robust Features](https://www.g2.com/survey_responses/amazon-quicksight-review-11360363)"** **Rating:** 4.0/5.0 stars *— Dilip Kumar P.* [Read full review](https://www.g2.com/survey_responses/amazon-quicksight-review-11360363) --- #### What Are G2 Users Discussing About Amazon QuickSight? - [What is Amazon QuickSight used for?](https://www.g2.com/discussions/what-is-amazon-quicksight-used-for) - 2 comments, 1 upvote - [What is new in QuickSight?](https://www.g2.com/discussions/what-is-new-in-quicksight) - 1 comment, 1 upvote - [Is AWS QuickSight free?](https://www.g2.com/discussions/is-aws-quicksight-free) - 2 comments, 1 upvote - [How does AWS QuickSight work?](https://www.g2.com/discussions/how-does-aws-quicksight-work) - 2 comments, 1 upvote - [What is Amazon QuickSight?](https://www.g2.com/discussions/what-is-amazon-quicksight) - 2 comments, 1 upvote ### 4. [Adobe Analytics](https://www.g2.com/products/adobe-analytics/reviews) Adobe Analytics empowers marketing, product, and business teams with insights to understand their customers and the journeys they take across digital channels, products, content, and services. From digital data collection and relational clickstream processing to in-depth analysis, and reporting, Adobe Analytics helps you understand visitor engagement across your digital properties — making it possible to optimize digital marketing strategies, improve user experience, and drive business growth. Features: - Collect and ingest behavioral data in real-time from your web and mobile channels. - Automatically convert raw data for unlimited analysis to discover customer patterns, spot anomalies, identify friction in your digital experiences, and uncover insights from digital journeys. - Equip marketers and analysts with AI capabilities that speed through analyses so they can quickly and confidently generate insights to improve the digital experience. - Integrate and share insights, segments, and outputs from your data across other business applications. **Average Rating:** 4.2/5.0 **Total Reviews:** 1,173 **How Do G2 Users Rate Adobe Analytics?** - **Has the product been a good partner in doing business?:** 8.0/10 (Category avg: 8.9/10) - **AI Text Summarization:** 9.1/10 (Category avg: 8.1/10) - **Algorithms:** 8.6/10 (Category avg: 8.5/10) - **AI Text Generation:** 8.8/10 (Category avg: 8.1/10) **Who Is the Company Behind Adobe Analytics?** - **Seller:** [Adobe](https://www.g2.com/sellers/adobe) - **Company Website:** https://adobe.com - **Year Founded:** 1982 - **HQ Location:** San Jose, CA - **Twitter:** @Adobe (956,842 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1480/ (42,087 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Analyst - **Top Industries:** Marketing and Advertising, Information Technology and Services - **Company Size:** 43% Enterprise, 30% Mid-Market #### What Are Adobe Analytics's Pros and Cons? **Pros:** - Insights (84 reviews) - Analytics (77 reviews) - Ease of Use (74 reviews) - Features (59 reviews) - Reporting (37 reviews) **Cons:** - Learning Curve (51 reviews) - Steep Learning Curve (27 reviews) - Expensive (23 reviews) - Slow Performance (23 reviews) - Complexity (18 reviews) ### What Do G2 Reviewers Say About Adobe Analytics? *AI-generated summary from verified user reviews* **Pros:** - Users value the **advanced segmentation and customizable dashboards** of Adobe Analytics, enhancing data analysis and visualization capabilities. - Users commend **advanced segmentation and customizable dashboards** in Adobe Analytics for simplifying complex data analysis and visualization. - Users value the **ease of use** of Adobe Analytics, enabling effective data analysis and seamless integration with other systems. - Users appreciate the **customized reporting and comprehensive data analysis** features of Adobe Analytics for informed decision-making. - Users value the **detailed and customizable reporting** in Adobe Analytics, facilitating informed decisions and optimizing strategies effectively. **Cons:** - Users find a **steep learning curve** , requiring dedicated technical staff and creating bottlenecks in data tracking. - Users highlight a **steep learning curve** requiring significant training, complicating onboarding for new users and casual observers. - Users find the **high cost** of Adobe Analytics to be prohibitive, especially for smaller teams. - Users experience **slow performance** with Adobe Analytics, facing delays in data updates and report generation, affecting efficiency. - Users often find Adobe Analytics' **interface and reporting setup complex** , making it challenging for new users to extract insights quickly. #### What Are Recent G2 Reviews of Adobe Analytics? **"[Powerful, Detailed Insights with Customizable Dashboards in Adobe Analytics](https://www.g2.com/survey_responses/adobe-analytics-review-12644645)"** **Rating:** 4.5/5.0 stars *— Poorvaa M.* [Read full review](https://www.g2.com/survey_responses/adobe-analytics-review-12644645) --- **"[Adobe Analytics Turns User Data Into Actionable Insights](https://www.g2.com/survey_responses/adobe-analytics-review-13164783)"** **Rating:** 4.5/5.0 stars *— Hiten M.* [Read full review](https://www.g2.com/survey_responses/adobe-analytics-review-13164783) --- #### What Are G2 Users Discussing About Adobe Analytics? - [What is Adobe Analytics used for?](https://www.g2.com/discussions/what-is-adobe-analytics-used-for) - 2 comments ### 5. [IBM Cognos Analytics](https://www.g2.com/products/ibm-cognos-analytics/reviews) IBM Cognos Analytics is a business intelligence and analytics solution that uses agentic AI to help teams transform trusted data into actionable insights, build governed analytical applications, and make better decisions. Teams can explore data, monitor KPIs, analyze performance, forecast trends, and share insights across the business. The solution is built for business leaders, analysts, report authors, IT teams, and data governance teams that need governed reporting, self-service analytics, data modeling, and flexible deployment options. Common use cases include enterprise reporting, operational reporting, financial reporting, dashboarding, performance management, forecasting, and governed self-service analytics. It supports both centralized BI teams and distributed users who need consistent access to trusted analytics. Key capabilities: 1. Create governed reports and dashboards: Build, schedule, distribute, and manage reports, dashboards, and visualizations for teams, executives, and stakeholders. Support routine reporting, business reviews, and purpose-built analytical applications with consistent information. 2. Explore data with control: Use self-service analytics, certified data models, governed metrics, access controls, and auditability to keep reporting consistent across teams and departments. 3. Analyze and forecast faster: Use natural-language assistance, automated insights, and forecasting to help users understand data faster in supported versions and deployments. 4. Put Reporting Agents to work: Use agentic AI capabilities in supported versions and deployments to find reports, summarize results, share insights, and create or refine reports using natural language. 5. Deploy where the business needs it: Run Cognos Analytics in on-premises, IBM-hosted, hybrid, or certified container environments to align with infrastructure, security, and governance requirements. Cognos Analytics helps organizations reduce repetitive reporting work, improve consistency across metrics and dashboards, and make governed data analytics easier to access across the business. **Average Rating:** 4.1/5.0 **Total Reviews:** 438 **How Do G2 Users Rate IBM Cognos Analytics?** - **Has the product been a good partner in doing business?:** 7.8/10 (Category avg: 8.9/10) - **AI Text Summarization:** 8.0/10 (Category avg: 8.1/10) - **Algorithms:** 8.6/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.9/10 (Category avg: 8.1/10) **Who Is the Company Behind IBM Cognos Analytics?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Company Website:** https://www.ibm.com - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer, Analyst - **Top Industries:** Information Technology and Services, Financial Services - **Company Size:** 57% Enterprise, 26% Mid-Market #### What Are IBM Cognos Analytics's Pros and Cons? **Pros:** - Ease of Use (36 reviews) - Report Generation (17 reviews) - Analytics (15 reviews) - Data Visualization (15 reviews) - User Interface (12 reviews) **Cons:** - Learning Curve (18 reviews) - Learning Difficulty (10 reviews) - Slow Performance (9 reviews) - Complexity (8 reviews) - Complex Usage (6 reviews) ### What Do G2 Reviewers Say About IBM Cognos Analytics? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of IBM Cognos Analytics, enjoying intuitive features for reporting and analysis. - Users appreciate the **quick and easy report generation** capabilities of IBM Cognos Analytics, enhancing their data analysis experience. - Users appreciate the **in-depth adaptable dashboards** of IBM Cognos Analytics for generating insightful reports and visuals. - Users value the **effortless data visualization** of IBM Cognos Analytics, enhancing understanding through engaging and adaptable dashboards. - Users value the **intuitive user interface** of IBM Cognos Analytics, enhancing data comprehension and report creation efforts. **Cons:** - Users find the **learning curve steep** , making initial navigation and integration with other software challenging. - Users find the **learning difficulty** of IBM Cognos Analytics challenging, requiring substantial training and patience for effective use. - Users experience **slow performance** with IBM Cognos Analytics, especially with complex reports and large data sets. - Users find the **complexity** of building reports in IBM Cognos Analytics a significant barrier due to steep learning curves. - Users find the **complex usage** of IBM Cognos Analytics challenging, particularly for new users navigating advanced features. #### What Are Recent G2 Reviews of IBM Cognos Analytics? **"[Powerful, Scalable Analytics with Interactive Dashboards and Strong Governance](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-12770018)"** **Rating:** 4.0/5.0 stars *— Arkajit D.* [Read full review](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-12770018) --- **"[Powerful Reporting, Less Modern Interface](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-13048146)"** **Rating:** 4.0/5.0 stars *— Nunna H.* [Read full review](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-13048146) --- #### What Are G2 Users Discussing About IBM Cognos Analytics? - [What is IBM Cognos Analytics with Watson used for?](https://www.g2.com/discussions/what-is-ibm-cognos-analytics-with-watson-used-for) - 1 comment ### 6. [GoodData.AI](https://www.g2.com/products/gooddata-ai/reviews) GoodData is the full-stack, AI-native decision intelligence platform that helps businesses turn data into actionable, enterprise-grade insights. Designed for governed, scalable analytics, GoodData enables organizations to build, operationalize, and embed decisions, workflows, and AI agents directly within products and business workflows. The platform combines Analytics as Code, a governed semantic and metrics layer, APIs, SDKs, and open AI interoperability to help teams create composable analytics and AI experiences across products, workflows, and customer environments. From embedded analytics and dashboards to assistants, AI workflows, and interoperable agents, GoodData gives teams the foundation to move from insight to action with governance, performance, and deployment flexibility built in. Today, GoodData serves over 140,000 companies and 3.2 million users worldwide. **Average Rating:** 4.3/5.0 **Total Reviews:** 597 **How Do G2 Users Rate GoodData.AI?** - **Has the product been a good partner in doing business?:** 8.4/10 (Category avg: 8.9/10) - **Algorithms:** 6.7/10 (Category avg: 8.5/10) **Who Is the Company Behind GoodData.AI?** - **Seller:** [GoodData.AI](https://www.g2.com/sellers/gooddata-ai) - **Company Website:** https://www.gooddata.ai/ - **Year Founded:** 2007 - **HQ Location:** San Francisco, CA - **Twitter:** @gooddata (1 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/202760/ (281 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Product Manager - **Top Industries:** Computer Software, Consumer Services - **Company Size:** 44% Mid-Market, 40% Small-Business #### What Are GoodData.AI's Pros and Cons? **Pros:** - Ease of Use (52 reviews) - Data Visualization (34 reviews) - Integrations (34 reviews) - Intuitive (30 reviews) - Customization (28 reviews) **Cons:** - Learning Curve (28 reviews) - Learning Difficulty (19 reviews) - Missing Features (19 reviews) - Complexity (13 reviews) - Limited Customization (12 reviews) ### What Do G2 Reviewers Say About GoodData.AI? *AI-generated summary from verified user reviews* **Pros:** - Users find the **ease of use** of GoodData.AI impressive, with an intuitive interface that enhances their business operations. - Users appreciate the **easy-to-use data visualization** features of GoodData.AI, enhancing accessibility for trend analysis and reporting. - Users value the **quick integration** of GoodData.AI, enhancing workflow with seamless connections to various systems. - Users highlight the **intuitive user interface** of GoodData.AI, making it easy for newcomers to utilize its features. - Users value the **customization capabilities** of GoodData.AI, enhancing flexibility and enabling tailored business insights. **Cons:** - Users find the **learning curve steep** for GoodData.AI, especially for those unfamiliar with data modeling concepts. - Users find **learning GoodData.AI challenging** , especially those with backgrounds in non-relational databases, due to its complexity. - Users find the **missing features** of GoodData.AI frustrating, limiting customization and functionality for workflows and graphics. - Users find GoodData.AI's interface **complex** , especially when dealing with advanced features and data relationships. - Users find the **limited customization** options in GoodData.AI restrictive, hindering their ability to tailor the product effectively. #### What Are Recent G2 Reviews of GoodData.AI? **"[Mosaic & Semantic Layer Unite Our Data, Plus Helpful AI Dashboard Suggestions](https://www.g2.com/survey_responses/gooddata-ai-review-12912613)"** **Rating:** 5.0/5.0 stars *— Jeff P.* [Read full review](https://www.g2.com/survey_responses/gooddata-ai-review-12912613) --- **"[Embedded Dashboards and Consistent Metrics That Cut Support Tickets](https://www.g2.com/survey_responses/gooddata-ai-review-13032302)"** **Rating:** 5.0/5.0 stars *— Yash G.* [Read full review](https://www.g2.com/survey_responses/gooddata-ai-review-13032302) --- ### 7. [Amazon Forecast](https://www.g2.com/products/amazon-forecast/reviews) Amazon Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts. **Average Rating:** 4.3/5.0 **Total Reviews:** 102 **How Do G2 Users Rate Amazon Forecast?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) - **AI Text Summarization:** 8.8/10 (Category avg: 8.1/10) - **Algorithms:** 8.7/10 (Category avg: 8.5/10) - **AI Text Generation:** 9.6/10 (Category avg: 8.1/10) **Who Is the Company Behind Amazon Forecast?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,232,483 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (147,094 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 49% Small-Business, 37% Mid-Market #### What Are Amazon Forecast's Pros and Cons? **Pros:** - Ease of Use (14 reviews) - Forecasting Accuracy (13 reviews) - Accuracy (11 reviews) - Machine Learning (10 reviews) - Quality (7 reviews) **Cons:** - Expensive (11 reviews) - Complexity (9 reviews) - Learning Curve (6 reviews) - Cost Issues (5 reviews) - Large Dataset Handling (5 reviews) ### What Do G2 Reviewers Say About Amazon Forecast? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Amazon Forecast, enabling quick and accurate predictions without extensive expertise. - Users appreciate the **forecasting accuracy** of Amazon Forecast, enabling effective planning and decision-making with ease. - Users appreciate the **accuracy of time-series predictions** in Amazon Forecast, simplifying demand planning and decision-making. - Users appreciate the **easy integration and accurate predictions** of Amazon Forecast, simplifying demand planning with minimal ML expertise. - Users value the **high accuracy** of Amazon Forecast, which utilizes advanced ML technology for reliable results. **Cons:** - Users find Amazon Forecast **expensive** for large datasets and frequent predictions, raising concerns about affordability. - Users find the **complex setup process** of Amazon Forecast challenging, especially for those new to AWS. - Users experience a challenging **learning curve** due to complex configurations and understanding data schemas before optimal use. - Users highlight **cost issues** with Amazon Forecast, emphasizing complex pricing and potential for budget surprises with large datasets. - Users find that managing **large datasets can lead to escalating costs** and a steep learning curve with Amazon Forecast. #### What Are Recent G2 Reviews of Amazon Forecast? **"[Accurate ML Forecasting Without the Expertise—Seamless AWS Integration](https://www.g2.com/survey_responses/amazon-forecast-review-12255988)"** **Rating:** 4.5/5.0 stars *— Mahmoud H.* [Read full review](https://www.g2.com/survey_responses/amazon-forecast-review-12255988) --- **"[Amazon Forecast: Game-Changing Sales Predictor for Training Pros](https://www.g2.com/survey_responses/amazon-forecast-review-12216415)"** **Rating:** 4.5/5.0 stars *— Dhanesh V.* [Read full review](https://www.g2.com/survey_responses/amazon-forecast-review-12216415) --- ### 8. [SAP Analytics Cloud](https://www.g2.com/products/sap-analytics-cloud/reviews) With the SAP Analytics Cloud solution, you can bring together analytics and planning with unique integration to SAP applications and smooth access to heterogenous data sources. As the analytics and planning solution within SAP Business Technology Platform, SAP Analytics Cloud supports trusted insights and integrated planning processes enterprise-wide to help you make decisions without doubt. **Average Rating:** 4.2/5.0 **Total Reviews:** 750 **How Do G2 Users Rate SAP Analytics Cloud?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **AI Text Summarization:** 8.9/10 (Category avg: 8.1/10) - **Algorithms:** 8.0/10 (Category avg: 8.5/10) - **AI Text Generation:** 8.7/10 (Category avg: 8.1/10) **Who Is the Company Behind SAP Analytics Cloud?** - **Seller:** [SAP](https://www.g2.com/sellers/sap) - **Company Website:** https://www.sap.com/ - **Year Founded:** 1972 - **HQ Location:** Walldorf - **Twitter:** @SAP (297,052 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/sap/ (141,955 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Senior Consultant, Consultant - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 49% Enterprise, 28% Mid-Market #### What Are SAP Analytics Cloud's Pros and Cons? **Pros:** - Ease of Use (67 reviews) - Data Analysis (51 reviews) - Data Visualization (50 reviews) - Easy Integrations (39 reviews) - Analytics (38 reviews) **Cons:** - Slow Performance (36 reviews) - Learning Curve (34 reviews) - Learning Difficulty (32 reviews) - Performance Issues (32 reviews) - Large Dataset Handling (30 reviews) ### What Do G2 Reviewers Say About SAP Analytics Cloud? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** in SAP Analytics Cloud, facilitating effortless data understanding and streamlined reporting. - Users appreciate the **wide range of data connectivity options** in SAP Analytics Cloud, enhancing integration and analytics capabilities. - Users value the **interactive dashboards** of SAP Analytics Cloud, which enhance data clarity and user customization. - Users value the **easy integrations** of SAP Analytics Cloud, enjoying seamless connectivity and efficient data analysis across projects. - Users appreciate the **wide range of data connectivity and predictive analytics** in SAP Analytics Cloud for effective decision-making. **Cons:** - Users experience **slow performance** with SAP Analytics Cloud, particularly when working with complex datasets and large models. - Users face a **steep learning curve** with SAP Analytics Cloud, requiring training to navigate its complex features effectively. - Users find the **steep learning curve** challenging, especially without guidance for navigating SAP Analytics Cloud's features. - Users experience significant **performance issues** with SAP Analytics Cloud, particularly with large datasets and complex calculations. - Users experience **slow performance with large datasets** , making complex analyses cumbersome and time-consuming. #### What Are Recent G2 Reviews of SAP Analytics Cloud? **"[SAP Analytics Cloud Clean Dashboards and Powerful Real Time Analytics in One Place](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12817514)"** **Rating:** 5.0/5.0 stars *— Muzammil M.* [Read full review](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12817514) --- **"[Reliable & User-Friendly Analytics Tool](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12885706)"** **Rating:** 4.0/5.0 stars *— sagar i.* [Read full review](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12885706) --- #### What Are G2 Users Discussing About SAP Analytics Cloud? - [What is SAP Analytics Cloud used for?](https://www.g2.com/discussions/what-is-sap-analytics-cloud-used-for) - 2 comments - [What is SAP Lumira used for?](https://www.g2.com/discussions/sap-lumira-what-is-sap-lumira-used-for) - 1 comment, 1 upvote - [What is SAP Analytics Hub used for?](https://www.g2.com/discussions/what-is-sap-analytics-hub-used-for) - 1 comment - [How does SAP Analytics calculate average cloud?](https://www.g2.com/discussions/how-does-sap-analytics-calculate-average-cloud) - [What is predictive analytics software?](https://www.g2.com/discussions/sap-predictive-analytics-what-is-predictive-analytics-software) - 1 comment ### 9. [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) BigQuery is an AI-ready, petabyte-scale, and cost-effective data warehouse that lets you run analytics over vast amounts of data in near real time. Store 10 GiB of data and run up to 1 TiB of queries for free per month. **Average Rating:** 4.5/5.0 **Total Reviews:** 1,144 **How Do G2 Users Rate Google Cloud BigQuery?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **AI Text Summarization:** 7.6/10 (Category avg: 8.1/10) - **Algorithms:** 8.8/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.4/10 (Category avg: 8.1/10) **Who Is the Company Behind Google Cloud BigQuery?** - **Seller:** [Google](https://www.g2.com/sellers/google) - **Year Founded:** 1998 - **HQ Location:** Mountain View, CA - **Twitter:** @google (31,899,995 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1441/ (341,888 employees on LinkedIn®) - **Ownership:** NASDAQ:GOOG **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 38% Enterprise, 35% Mid-Market #### What Are Google Cloud BigQuery's Pros and Cons? **Pros:** - Ease of Use (129 reviews) - Speed (126 reviews) - Integrations (110 reviews) - Fast Querying (105 reviews) - Query Efficiency (100 reviews) **Cons:** - Expensive (112 reviews) - Query Issues (65 reviews) - Cost Management (52 reviews) - Cost Issues (51 reviews) - Learning Curve (49 reviews) ### What Do G2 Reviewers Say About Google Cloud BigQuery? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Google Cloud BigQuery, enabling quick analysis of massive datasets without hassle. - Users appreciate the **exceptional speed** of BigQuery, allowing for quick processing of large datasets seamlessly. - Users love the **easy integration** with Google Cloud services, enabling smooth data analysis and management. - Users appreciate the **fast querying capabilities** of Google Cloud BigQuery, allowing effortless analysis of massive datasets. - Users appreciate the **query efficiency** of BigQuery, effortlessly processing complex queries on massive datasets with speed. **Cons:** - Users find the **costs can escalate quickly** with Google Cloud BigQuery, requiring careful query optimization to manage expenses. - Users struggle with **query issues** in BigQuery, facing rising costs and challenges in query optimization and troubleshooting. - Users find **cost management challenging** with Google Cloud BigQuery due to unpredictable pricing and incidents of unexpected charges. - Users experience **cost issues** with Google Cloud BigQuery, struggling with unexpected high bills and limited pricing visibility. - Users find the **steep learning curve** of Google Cloud BigQuery challenging, particularly for advanced features and optimization techniques. #### What Are Recent G2 Reviews of Google Cloud BigQuery? **"[Easy-to-Use Cloud Tool with Shareable, Saved Queries](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)"** **Rating:** 4.0/5.0 stars *— Reetika P.* [Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418) --- **"[Scalable, Secure BigQuery That Connects Seamlessly Across Services](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)"** **Rating:** 5.0/5.0 stars *— Aayush M.* [Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747) --- #### What Are G2 Users Discussing About Google Cloud BigQuery? - [Is Big Query free?](https://www.g2.com/discussions/is-big-query-free) - 3 comments, 1 upvote - [Is BigQuery part of Google Cloud Platform?](https://www.g2.com/discussions/is-bigquery-part-of-google-cloud-platform) - 2 comments, 2 upvotes - [What is Google BigQuery based on?](https://www.g2.com/discussions/what-is-google-bigquery-based-on) - 1 comment - [What is Google BigQuery used for?](https://www.g2.com/discussions/what-is-google-bigquery-used-for) - 1 comment ### 10. [Nixtla](https://www.g2.com/products/nixtla/reviews) TimeGPT is a cutting-edge foundation model specifically designed for time series forecasting and anomaly detection. This innovative solution empowers users to harness the full potential of their time series data, enabling more informed decision-making across various domains. With its advanced capabilities, TimeGPT stands out as a pivotal tool for organizations looking to optimize their data-driven strategies. Targeted at data scientists, analysts, and business decision-makers, TimeGPT caters to a wide range of industries, including finance, energy, and meteorology. Its ability to process and analyze vast amounts of time series data makes it an invaluable resource for those seeking to improve operational efficiency, enhance predictive accuracy, and identify unusual patterns that may indicate underlying issues. Whether it’s forecasting stock prices, predicting energy consumption, or analyzing weather trends, TimeGPT provides the necessary tools to tackle complex time series challenges. One of the key features of TimeGPT is its zero-shot inference capability, which allows users to generate forecasts and detect anomalies without the need for prior training data. This feature significantly reduces the time and resources typically required for model training, enabling users to quickly gain insights from their data. Additionally, TimeGPT has been extensively trained on over 100 billion time series data points, ensuring that it can deliver reliable and accurate predictions across various contexts. TimeGPT also offers fine-tuning options, allowing users to adapt the model to their specific datasets. This flexibility ensures that organizations can tailor the model to their unique time series characteristics, enhancing its predictive performance. Furthermore, the model supports the integration of exogenous variables, which can improve forecast accuracy by accounting for external factors that may influence the data. With robust API access, TimeGPT can be seamlessly integrated into existing applications, making it easy for organizations to leverage its capabilities. It is also compatible with Azure Studio and can be deployed on private infrastructure, providing users with the flexibility to choose the deployment method that best suits their needs. The ability to forecast multiple time series simultaneously further optimizes workflows, allowing organizations to manage resources effectively while enhancing their analytical capabilities. In addition to its forecasting prowess, TimeGPT excels in anomaly detection, automatically identifying unusual patterns in time series data. This feature is particularly beneficial for organizations that need to monitor systems in real-time and respond swiftly to potential issues. By incorporating exogenous features, users can further enhance the model's performance, ensuring that they are equipped to handle the complexities of their time series data. **Average Rating:** 4.7/5.0 **Total Reviews:** 50 **How Do G2 Users Rate Nixtla?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 8.9/10) - **AI Text Summarization:** 4.3/10 (Category avg: 8.1/10) - **Algorithms:** 9.6/10 (Category avg: 8.5/10) - **AI Text Generation:** 4.6/10 (Category avg: 8.1/10) **Who Is the Company Behind Nixtla?** - **Seller:** [Nixtla](https://www.g2.com/sellers/nixtla) - **Company Website:** https://www.nixtla.io/ - **Year Founded:** 2021 - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/nixtlainc (33 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Scientist - **Top Industries:** Computer Software, Retail - **Company Size:** 44% Enterprise, 38% Small-Business #### What Are Nixtla's Pros and Cons? **Pros:** - Ease of Use (30 reviews) - Easy Integrations (16 reviews) - Customer Support (15 reviews) - Machine Learning (13 reviews) - Implementation Ease (12 reviews) **Cons:** - Missing Features (7 reviews) - Expensive (6 reviews) - Lack of Guidance (5 reviews) - Limited Features (5 reviews) - Learning Curve (3 reviews) ### What Do G2 Reviewers Say About Nixtla? *AI-generated summary from verified user reviews* **Pros:** - Users find Nixtla's tools remarkably **easy to use** , simplifying their forecasting workflows with minimal coding effort. - Users commend **easy integrations** of Nixtla's tools, streamlining workflows and boosting productivity in various environments. - Users appreciate the **responsive customer support** from Nixtla, ensuring they receive timely assistance and guidance. - Users appreciate the **impressive selection of models** in Nixtla, enabling easy and effective hands-on forecasting education. - Users value the **remarkable ease of implementation** of Nixtla, enabling fast prototyping and seamless integration with existing systems. **Cons:** - Users note a **lack of essential features** in Nixtla, particularly for beginners and enterprise users. - Users find Nixtla **quite expensive** , making it less accessible for smaller companies or non-critical forecasting needs. - Users find a significant **lack of guidance** in Nixtla, particularly for advanced and complex use cases. - Users find the product's **limited features** restrict its utility, particularly for comprehensive data science tasks. - Users find the **learning curve steep** due to limited documentation for advanced use cases and configuration difficulties. #### What Are Recent G2 Reviews of Nixtla? **"[Effortless Precision in Market Forecasting](https://www.g2.com/survey_responses/nixtla-review-11452193)"** **Rating:** 5.0/5.0 stars *— Brett R.* [Read full review](https://www.g2.com/survey_responses/nixtla-review-11452193) --- **"[Impressive Forecasting for Environmental Data, but Geospatial Support Needs Improvement](https://www.g2.com/survey_responses/nixtla-review-11907658)"** **Rating:** 4.0/5.0 stars *— Gloria C.* [Read full review](https://www.g2.com/survey_responses/nixtla-review-11907658) --- ### 11. [Minitab Statistical Software](https://www.g2.com/products/minitab-statistical-software/reviews) Minitab Statistical Software is a comprehensive data analysis and statistical solution designed to assist users in exploring data, identifying trends, and making informed, data-driven decisions. This software caters to a diverse audience, ranging from beginners to seasoned analysts, by combining powerful statistical methods with an intuitive interface. This design approach simplifies complex analyses while ensuring depth and accuracy are not compromised. The capabilities of Minitab are extensive, encompassing a variety of statistical techniques such as descriptive statistics, hypothesis testing, regression analysis, ANOVA, time series analysis, design of experiments (DOE), reliability analysis, and predictive analytics. The software's guided workflows and Assistant feature are particularly beneficial, as they help users select appropriate tools, interpret results effectively, and communicate findings in a clear manner. This accessibility makes advanced analytics feasible for users across different skill levels, promoting a culture of data-driven decision-making within organizations. Minitab is available in both desktop and cloud-based versions, providing users with the flexibility to work from various locations while ensuring secure access to their data and analyses. The cloud version enhances collaboration among teams by allowing them to share projects and standardize analyses without the need for local installation. This feature is particularly advantageous for organizations with remote teams or those looking to streamline their analytical processes. The software also includes built-in data preparation tools that facilitate the cleaning and organization of data, which is crucial for accurate analysis. Furthermore, Minitab seamlessly integrates with other Minitab solutions and supports quality improvement methodologies such as Six Sigma. This integration helps organizations enhance their processes, reduce variation, and achieve measurable business outcomes. By providing a robust suite of tools and features, Minitab Statistical Software stands out as a valuable resource for organizations aiming to leverage data for strategic advantage. **Average Rating:** 4.6/5.0 **Total Reviews:** 220 **How Do G2 Users Rate Minitab Statistical Software?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **AI Text Summarization:** 7.4/10 (Category avg: 8.1/10) - **Algorithms:** 8.3/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.3/10 (Category avg: 8.1/10) **Who Is the Company Behind Minitab Statistical Software?** - **Seller:** [Minitab](https://www.g2.com/sellers/minitab-14ca02fe-fdeb-44c4-b0db-904058d0221b) - **Company Website:** https://www.minitab.com - **Year Founded:** 1972 - **HQ Location:** State College, Pennsylvania, United States - **Twitter:** @Minitab (5,017 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/39142/ (732 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Quality Manager - **Top Industries:** Automotive, Manufacturing - **Company Size:** 46% Enterprise, 32% Mid-Market #### What Are Minitab Statistical Software's Pros and Cons? **Pros:** - Ease of Use (62 reviews) - Data Analysis (53 reviews) - Statistical Analysis (38 reviews) - Analysis (32 reviews) - Analysis Capabilities (30 reviews) **Cons:** - Expensive (23 reviews) - Learning Curve (22 reviews) - Complexity (13 reviews) - Not User-Friendly (13 reviews) - Data Management Issues (10 reviews) ### What Do G2 Reviewers Say About Minitab Statistical Software? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **ease of use** of Minitab, highlighting its intuitive interface and helpful resources for efficient analysis. - Users praise Minitab for its **ease of use** , enhancing their overall data analysis experience significantly. - Users value the **helpful guides and assistants** in Minitab, enhancing their data analysis experience significantly. - Users value Minitab for its **comprehensive tools** that enhance data-driven decision-making in manufacturing and quality analysis. - Users value Minitab's **robust analysis capabilities** , making statistical data processing straightforward and effective for decision-making. **Cons:** - Users find the **licensing fees expensive** , especially when usage is intermittent and features are underutilized. - Users find a **steep learning curve** with Minitab, highlighting the need for better training resources and usability improvements. - Users find Minitab's **complexity** challenging due to issues with hidden variables and clunky data manipulation features. - Users find Minitab’s interface **not user-friendly** , as confusing menus and outdated design hinder ease of use. - Users face **data management issues** in Minitab, complicating analysis and requiring re-runs with updated datasets. #### What Are Recent G2 Reviews of Minitab Statistical Software? **"[Audit-Ready Trend Analysis and Clear Statistical Outputs for APQR](https://www.g2.com/survey_responses/minitab-statistical-software-review-12736010)"** **Rating:** 4.0/5.0 stars *— Ajay K.* [Read full review](https://www.g2.com/survey_responses/minitab-statistical-software-review-12736010) --- **"[Minitab’s DOE Wizard Makes Complex Experiments Fast and Straightforward](https://www.g2.com/survey_responses/minitab-statistical-software-review-13070943)"** **Rating:** 5.0/5.0 stars *— Nikhil C.* [Read full review](https://www.g2.com/survey_responses/minitab-statistical-software-review-13070943) --- #### What Are G2 Users Discussing About Minitab Statistical Software? - [What improvements would you suggest for Minitab to better meet your data analysis needs?](https://www.g2.com/discussions/what-improvements-would-you-suggest-for-minitab-to-better-meet-your-data-analysis-needs) - [What is Minitab Statistical Software used for?](https://www.g2.com/discussions/what-is-minitab-statistical-software-used-for) - 1 comment - [Is Minitab free for students?](https://www.g2.com/discussions/minitab-statistical-software-is-minitab-free-for-students) - 2 comments - [Is Minitab free for students?](https://www.g2.com/discussions/is-minitab-free-for-students) - [What Minitab 19?](https://www.g2.com/discussions/minitab-statistical-software-what-minitab-19) ### 12. [IBM SPSS Statistics](https://www.g2.com/products/ibm-spss-statistics/reviews) IBM SPSS Statistics is an end-to-end statistical solution that simplifies advanced statistical analysis across industries for users of any statistical expertise. It offers comprehensive resources, expert support, and proven reliability to transform complex data into impactful decisions IBM SPSS Statistics recent version 32 release comes up with powerful new features such as AI Output Assistant, Mediation Analysis, Curated Help Designer and many advanced algorithms. IBM SPSS Statistics • offers an easy to use drag and drop interface along with AI Output Assistant to interpret complex statistical output in easy language. • simplifies complex data analysis using advanced statistical techniques that performs data preparation and management, to analysis and reporting. • performs predictive analysis using advanced forecasting procedures to uncover patterns and predict future trends. • creates compelling visual representations to identify trends, derive accurate conclusions and deliver graphs and presentation-ready reports Explore how both individuals and organizations spanning across Industries can simply complex statistical test through an easy to use, accurate ,reliable and secure solution. Use Cases 1. Market Research - Statistical procedures highlighting how to do market research with IBM SPSS 2. Client Acquisition – Emphasizes on how can organizations can acquire more clients and understand consumer behavior 3. Forecasting – Analyze historical sales data, evaluate key trends, predict outcomes relevant to inventory planning 4. Healthcare - Enabling healthcare organizations to improve patient outcomes 5. Government - Empowering Government institutions to take smarter policy decisions 6. Supply Chain - Utilize Statistical Algorithms to make data-driven decisions across procurement, inventory, logistics, and demand planning. Visit here to see what's new in v32 - https://www.ibm.com/products/spss-statistics/whats-new **Average Rating:** 4.2/5.0 **Total Reviews:** 893 **How Do G2 Users Rate IBM SPSS Statistics?** - **Has the product been a good partner in doing business?:** 8.0/10 (Category avg: 8.9/10) - **AI Text Summarization:** 9.7/10 (Category avg: 8.1/10) - **Algorithms:** 7.7/10 (Category avg: 8.5/10) - **AI Text Generation:** 9.7/10 (Category avg: 8.1/10) **Who Is the Company Behind IBM SPSS Statistics?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Company Website:** https://www.ibm.com - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Research Assistant, Assistant Professor - **Top Industries:** Higher Education, Research - **Company Size:** 42% Enterprise, 30% Mid-Market #### What Are IBM SPSS Statistics's Pros and Cons? **Pros:** - Ease of Use (33 reviews) - Statistical Analysis (19 reviews) - Data Management (15 reviews) - User Interface (13 reviews) - Analysis Capabilities (12 reviews) **Cons:** - Expensive (19 reviews) - Poor Visualization (12 reviews) - Learning Curve (11 reviews) - Outdated Interface (7 reviews) - Performance Issues (7 reviews) ### What Do G2 Reviewers Say About IBM SPSS Statistics? *AI-generated summary from verified user reviews* **Pros:** - Users love the **user-friendly interface** of IBM SPSS Statistics, making complex analysis accessible for all backgrounds. - Users appreciate the **user-friendly interface** of IBM SPSS Statistics, simplifying complex statistical analysis without coding requirements. - Users value the **superior data management and cleaning capabilities** that enhance accuracy and reliability in analysis. - Users value the **user-friendly interface** of IBM SPSS Statistics, making complex statistical tasks approachable and efficient. - Users appreciate the **easy-to-understand analysis capabilities** of IBM SPSS Statistics, simplifying complex statistical tasks for effective research. **Cons:** - Users find the **cost too high** , especially for small businesses needing effective data analysis solutions. - Users find the **poor visualization** in SPSS Statistics hampers usability and complicates data interpretation for stakeholders. - Users find the **learning curve steep** due to a lack of strong tutorials and complicated initial setup. - Users find the **interface outdated** and often clunky, making it challenging for new learners to adapt. - Users often experience **performance issues** with IBM SPSS Statistics, particularly when handling large datasets, impacting usability. #### What Are Recent G2 Reviews of IBM SPSS Statistics? **"[Efficient, Reliable Statistical Analysis with an Approachable UI in IBM SPSS Statistics](https://www.g2.com/survey_responses/ibm-spss-statistics-review-12829044)"** **Rating:** 4.0/5.0 stars *— Arkajit D.* [Read full review](https://www.g2.com/survey_responses/ibm-spss-statistics-review-12829044) --- **"[Powerful, User-Friendly Platform for Advanced Data Analysis and Reporting](https://www.g2.com/survey_responses/ibm-spss-statistics-review-12803842)"** **Rating:** 4.5/5.0 stars *— Konjengbam M.* [Read full review](https://www.g2.com/survey_responses/ibm-spss-statistics-review-12803842) --- #### What Are G2 Users Discussing About IBM SPSS Statistics? - [What is IBM SPSS Statistics used for?](https://www.g2.com/discussions/ibm-spss-statistics-what-is-ibm-spss-statistics-used-for) - 1 comment - [What are the features of statistical software?](https://www.g2.com/discussions/ibm-spss-statistics-what-are-the-features-of-statistical-software) - 1 comment - [What are the features of SPSS?](https://www.g2.com/discussions/what-are-the-features-of-spss) - 1 comment - [What statistical analysis is included in SPSS?](https://www.g2.com/discussions/what-statistical-analysis-is-included-in-spss) - 2 comments - [What is IBM SPSS Statistics used for?](https://www.g2.com/discussions/what-is-ibm-spss-statistics-used-for) - 1 comment, 1 upvote ### 13. [Clari](https://www.g2.com/products/clari/reviews) Clari+Salesloft is a category-transforming AI company architecting the future of revenue. By building the world’s first Predictive Revenue System, we help organizations move beyond fragmented applications and systems of record to a model that continuously drives and adapts revenue execution. Our platform captures deal data signals, and uses tailor-built AI to create the right context and drive action across sales teams. Instead of disconnected insights and siloed workflows, sales teams operate with shared understanding, faster decisions, and execution that stays aligned to the business. Trusted by thousands of enterprises including Adobe, 3M, IBM, and Zoom, Clari+Salesloft powers the forecast, surfaces pipeline risk, and drives proactive execution—returning thousands of hours to the field and enabling predictable, scalable growth. **Average Rating:** 4.6/5.0 **Total Reviews:** 5,503 **How Do G2 Users Rate Clari?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 8.9/10) - **Algorithms:** 10.0/10 (Category avg: 8.5/10) **Who Is the Company Behind Clari?** - **Seller:** [Salesloft](https://www.g2.com/sellers/salesloft) - **Year Founded:** 2011 - **HQ Location:** Atlanta, GA - **Twitter:** @Salesloft (18,437 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2296178/ (1,097 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Account Executive, Account Manager - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 47% Mid-Market, 41% Enterprise #### What Are Clari's Pros and Cons? **Pros:** - Ease of Use (722 reviews) - Forecasting (486 reviews) - Features (365 reviews) - Salesforce Integration (326 reviews) - Helpful (287 reviews) **Cons:** - Limitations (186 reviews) - Limited Customization (150 reviews) - Learning Curve (147 reviews) - Missing Features (147 reviews) - Salesforce Integration (131 reviews) ### What Do G2 Reviewers Say About Clari? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** in Clari for forecasting, appreciating its intuitive interface and seamless updates. - Users appreciate the **ease of use** in Clari's Forecasting, allowing quick updates and excellent tracking against quotas. - Users appreciate Clari for its **real-time updates and seamless Salesforce integration** , enhancing workflow efficiency and visibility in sales opportunities. - Users find the **Salesforce integration** invaluable for streamlined data management and enhanced forecasting capabilities within Clari. - Users find Clari **incredibly helpful** for easy forecasting and effective revenue management, simplifying admin tasks significantly. **Cons:** - Users experience **customization limitations** with Clari, making it difficult to meet unique business needs effectively. - Users find **limited customization** in Clari, hindering tailored solutions for unique business needs and team insights. - Users experience a **steep learning curve** with Clari due to initial configuration and a confusing UI layout. - Users find **missing features** in Clari, with limitations in filtering, customization, and mobile app functionality affecting their experience. - Users experience **inconsistent Salesforce data reflection** in Clari, leading to confusion and potential errors in reporting. #### What Are Recent G2 Reviews of Clari? **"[Clari has met and exceed our expectations for our GTM Oganization](https://www.g2.com/survey_responses/clari-review-10775002)"** **Rating:** 4.0/5.0 stars *— Eric M.* [Read full review](https://www.g2.com/survey_responses/clari-review-10775002) --- **"[Clari Platform Review from a RevOps Perspective](https://www.g2.com/survey_responses/clari-review-12400239)"** **Rating:** 5.0/5.0 stars *— Matt D.* [Read full review](https://www.g2.com/survey_responses/clari-review-12400239) --- #### What Are G2 Users Discussing About Clari? - [How does Groove's integration with Clari enhance sales and revenue operations?](https://www.g2.com/discussions/how-does-groove-s-integration-with-clari-enhance-sales-and-revenue-operations) - 1 comment - [How is Groove, a Clari Company being used to enhance operational efficiency and user experience in its specific field?](https://www.g2.com/discussions/how-is-groove-a-clari-company-being-used-to-enhance-operational-efficiency-and-user-experience-in-its-specific-field) - [How do I add groove to Gmail?](https://www.g2.com/discussions/how-do-i-add-groove-to-gmail) - 1 comment - [How much does groove cost?](https://www.g2.com/discussions/how-much-does-groove-cost) - 1 comment, 1 upvote - [What groove means in music?](https://www.g2.com/discussions/what-groove-means-in-music) - 7 comments ### 14. [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) Altair AI Studio (formerly RapidMiner Studio) is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an organization. Altair AI Studio includes: - Full generative AI functionality with access to hundreds of large language models (LLMs). - Intuitive and powerful drag-and-drop canvases that give users code-like control without complexity. - Award-winning auto ML with automated clustering, predictive modeling, feature engineering, and time series forecasting. - Data connectivity, exploration, and preparation. - Deploy and manage AI projects and models at enterprise scale. - Collaborate with team members in the same environment without having to worry about overwriting each other's work. - Unify the entire data science lifecycle from data exploration and machine learning to model operations and visualization and deploy in the cloud. Altair AI Studio helps users make powerful insights accessible to the entire organization and can scale seamlessly for users and enterprises. Altair AI studio enables organizations to derive significant value from AI with minimal cost and operational impact. **Average Rating:** 4.6/5.0 **Total Reviews:** 494 **How Do G2 Users Rate Altair AI Studio?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) - **AI Text Summarization:** 6.9/10 (Category avg: 8.1/10) - **Algorithms:** 8.6/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.2/10 (Category avg: 8.1/10) **Who Is the Company Behind Altair AI Studio?** - **Seller:** [Altair](https://www.g2.com/sellers/altair-186799f5-3238-493f-b3ad-b8cac484afd7) - **Company Website:** https://www.altair.com/ - **Year Founded:** 1985 - **HQ Location:** Troy, MI - **LinkedIn® Page:** https://www.linkedin.com/company/8323/ (2,774 employees on LinkedIn®) - **Ownership:** NASDAQ:ALTR **Who Uses This Product?** - **Who Uses This:** Student, Data Scientist - **Top Industries:** Higher Education, Education Management - **Company Size:** 42% Small-Business, 30% Mid-Market #### What Are Altair AI Studio's Pros and Cons? **Pros:** - Ease of Use (9 reviews) - Machine Learning (8 reviews) - AI Integration (6 reviews) - AI Technology (5 reviews) - Automation (5 reviews) **Cons:** - Complexity (4 reviews) - Large Dataset Handling (3 reviews) - Slow Performance (3 reviews) - Complexity Issues (2 reviews) - Complex Usage (2 reviews) ### What Do G2 Reviewers Say About Altair AI Studio? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Altair AI Studio, benefiting from its intuitive drag-and-drop interface. - Users value the **ease of using machine learning without coding** , making it accessible and beneficial for education and organizations. - Users value the **seamless AI integration** of Altair AI Studio, enhancing decision making and efficiency in data analysis. - Users value the **advanced machine learning and analytics** in Altair AI Studio, enhancing decision-making and efficiency. - Users value the **automation features** of Altair AI Studio, streamlining processes and enhancing data analysis efficiency. **Cons:** - Users find the **complexity** of Altair AI Studio challenging, especially with integration and performance issues. - Users often face **slow performance with large datasets** , which can impact their overall experience with Altair AI Studio. - Users report experiencing **slow performance** with Altair AI Studio, especially when working with large or complex datasets. - Users find the **complexity issues** of Altair AI Studio frustrating, especially due to limited support in Japanese. - Users find the **complex usage** of Altair AI Studio challenging due to steep learning curves and limited documentation. #### What Are Recent G2 Reviews of Altair AI Studio? **"[Essential Tool for Streamlined Sensor Analysis](https://www.g2.com/survey_responses/altair-ai-studio-review-12568188)"** **Rating:** 5.0/5.0 stars *— Ayçe M.* [Read full review](https://www.g2.com/survey_responses/altair-ai-studio-review-12568188) --- **"[Great tool for easy data analysis and testing of AI models](https://www.g2.com/survey_responses/altair-ai-studio-review-12942088)"** **Rating:** 4.5/5.0 stars *— Sanjeet S.* [Read full review](https://www.g2.com/survey_responses/altair-ai-studio-review-12942088) --- #### What Are G2 Users Discussing About Altair AI Studio? - [What is RapidMiner used for?](https://www.g2.com/discussions/what-is-rapidminer-used-for) - 1 comment - [What are the data mining tools?](https://www.g2.com/discussions/what-are-the-data-mining-tools) - [Is RapidMiner open source?](https://www.g2.com/discussions/is-rapidminer-open-source) - [How do you use the Rapid Miner?](https://www.g2.com/discussions/how-do-you-use-the-rapid-miner) - [Is Rapid Miner legit?](https://www.g2.com/discussions/is-rapid-miner-legit) ### 15. [Qlik Predict](https://www.g2.com/products/qlik-predict/reviews) Qlik AutoML (automated machine learning) brings AI-generated machine learning models and predictive analytics directly to your organization’s larger community of analytics users and teams, in a simple user experience focused on augmenting their intuition through machine intelligence. With AutoML, you can easily generate machine learning models, make predictions, and plan decisions – all within an intuitive, code-free user interface. Machine learning (ML) is a branch of artificial intelligence (AI) focused on the process of recognizing patterns in historical data to predict outcomes in the future. ML uses historically observed data as an input, applies a mathematical process against that data, and creates an output called a machine learning model based on patterns in historical data. This model can then be used to make future predictions and test scenarios. **Average Rating:** 4.4/5.0 **Total Reviews:** 78 **How Do G2 Users Rate Qlik Predict?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) - **AI Text Summarization:** 6.7/10 (Category avg: 8.1/10) - **Algorithms:** 8.2/10 (Category avg: 8.5/10) - **AI Text Generation:** 6.7/10 (Category avg: 8.1/10) **Who Is the Company Behind Qlik Predict?** - **Seller:** [Qlik](https://www.g2.com/sellers/qlik) - **Year Founded:** 1993 - **HQ Location:** Radnor, PA - **Twitter:** @qlik (64,130 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/10162/ (4,551 employees on LinkedIn®) - **Phone:** 1 (888) 994-9854 **Who Uses This Product?** - **Who Uses This:** Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 38% Enterprise, 31% Small-Business #### What Are Qlik Predict's Pros and Cons? **Pros:** - Automation (5 reviews) - Ease of Use (5 reviews) - AI Integration (4 reviews) - Machine Learning (4 reviews) - AI Capabilities (3 reviews) **Cons:** - Limited Customization (4 reviews) - Deployment Issues (2 reviews) - Lacking Features (2 reviews) - Required Knowledge (2 reviews) - Tool Limitations (2 reviews) ### What Do G2 Reviewers Say About Qlik Predict? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **automation features** of Qlik Predict, enabling quick and easy model building without extensive technical skills. - Users appreciate the **ease of use** of Qlik Predict, experiencing an intuitive no-code interface for hassle-free implementation. - Users value the **seamless AI integration** of Qlik Predict, enhancing efficiency in building and deploying predictive models. - Users appreciate the **intuitive no-code interface** of Qlik Predict, enabling quick model creation without technical expertise. - Users praise the **user-friendly AI capabilities** of Qlik Predict, enabling easy implementation of predictive models without coding. **Cons:** - Users find the **limited customization** of Qlik Predict restricts advanced functionalities and deployment flexibility. - Users face **deployment issues** with Qlik Predict, as options are limited and lack flexibility for external integrations. - Users note the **limited features** of Qlik Predict, especially in customization and deployment flexibility for advanced needs. - Users must have **required knowledge of data science** to effectively optimize models and interpret results with Qlik Predict. - Users find the **tool limitations** of Qlik Predict restrict customization and flexibility for advanced model development. #### What Are Recent G2 Reviews of Qlik Predict? **"[Qlik AutoML](https://www.g2.com/survey_responses/qlik-predict-review-11001365)"** **Rating:** 4.0/5.0 stars *— Anju P.* [Read full review](https://www.g2.com/survey_responses/qlik-predict-review-11001365) --- **"[Describe your experience in one short sentence.](https://www.g2.com/survey_responses/qlik-predict-review-11007278)"** **Rating:** 5.0/5.0 stars *— Cristian C.* [Read full review](https://www.g2.com/survey_responses/qlik-predict-review-11007278) --- #### What Are G2 Users Discussing About Qlik Predict? - [How does the NZXT Kraken work?](https://www.g2.com/discussions/how-does-the-nzxt-kraken-work) - [Is the NZXT Kraken water cooling?](https://www.g2.com/discussions/is-the-nzxt-kraken-water-cooling) - [Which NZXT Kraken is the best?](https://www.g2.com/discussions/which-nzxt-kraken-is-the-best) - [Does the NZXT Kraken come with fans?](https://www.g2.com/discussions/does-the-nzxt-kraken-come-with-fans) ### 16. [IBM SPSS Modeler](https://www.g2.com/products/ibm-spss-modeler/reviews) The IBM SPSS Modeler is a leading, visual data science and machine learning solution. It helps enterprises accelerate time to value and desired outcome by speeding the operational tasks for data scientists. Leading organizations worldwide rely on IBM for data discovery, predictive analytics, model management and deployment, and machine learning to monetize data assets. The IBM SPSS Modeler empowers organizations to tap data assets and modern applications with complete, out-of-box algorithms and models, suited for hybrid, multi-cloud environments with robust governance and security posture. • Take advantage of open source based innovation including R or Python • Empower data scientists of all skills – programmatic and visual • Exploit multi-cloud approach - on-prem, public or private clouds • Start small and scale to enterprise-wide, governed approach **Average Rating:** 4.0/5.0 **Total Reviews:** 128 **How Do G2 Users Rate IBM SPSS Modeler?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **AI Text Summarization:** 7.3/10 (Category avg: 8.1/10) - **Algorithms:** 8.0/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.3/10 (Category avg: 8.1/10) **Who Is the Company Behind IBM SPSS Modeler?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Top Industries:** Higher Education, Education Management - **Company Size:** 53% Enterprise, 24% Mid-Market #### What Are IBM SPSS Modeler's Pros and Cons? **Pros:** - Analysis Capabilities (1 reviews) - Analytics (1 reviews) - Data Access (1 reviews) - Data Management (1 reviews) - Data Visualization (1 reviews) **Cons:** - Expensive (1 reviews) - Expensive Licensing (1 reviews) ### What Do G2 Reviewers Say About IBM SPSS Modeler? *AI-generated summary from verified user reviews* **Pros:** - Users commend the **robust analytical modeling capabilities** of IBM SPSS Modeler, enhancing data manipulation and preparation tasks. - Users value the **seamless data connectivity** of IBM SPSS Modeler, enabling efficient data manipulation and analytical modeling. - Users value the **seamless data access** of IBM SPSS Modeler, allowing efficient data manipulation and integration. - Users value the **seamless data connection** in IBM SPSS Modeler, enhancing efficiency in data manipulation and analysis. - Users value the **seamless data connectivity and robust analytics** of IBM SPSS Modeler for efficient data manipulation. **Cons:** - Users find the **licensing costs** of IBM SPSS Modeler to be excessively high for each user. - Users are frustrated by the **expensive licensing** costs, which make the product less accessible for teams. #### What Are Recent G2 Reviews of IBM SPSS Modeler? **"[Seamless Data Integration and Powerful Analytics](https://www.g2.com/survey_responses/ibm-spss-modeler-review-12103509)"** **Rating:** 4.5/5.0 stars *— Verified User in Banking* [Read full review](https://www.g2.com/survey_responses/ibm-spss-modeler-review-12103509) --- **"[The best application for market research](https://www.g2.com/survey_responses/ibm-spss-modeler-review-8095256)"** **Rating:** 4.0/5.0 stars *— Basil E.* [Read full review](https://www.g2.com/survey_responses/ibm-spss-modeler-review-8095256) --- #### What Are G2 Users Discussing About IBM SPSS Modeler? - [What is IBM SPSS Modeler used for?](https://www.g2.com/discussions/ibm-spss-modeler-what-is-ibm-spss-modeler-used-for) - [What are the features of SPSS?](https://www.g2.com/discussions/ibm-spss-modeler-what-are-the-features-of-spss) - 1 comment - [What is IBM SPSS Modeler used for?](https://www.g2.com/discussions/what-is-ibm-spss-modeler-used-for) - 1 comment - [Is IBM SPSS Modeler free?](https://www.g2.com/discussions/is-ibm-spss-modeler-free) - 1 comment - [What is the difference between SPSS Statistics and Modeler?](https://www.g2.com/discussions/what-is-the-difference-between-spss-statistics-and-modeler) ### 17. [Salesloft](https://www.g2.com/products/salesloft/reviews) Clari + Salesloft is a category-transforming AI company architecting the future of revenue. By building the world’s first Predictive Revenue System, we help organizations move beyond fragmented applications and systems of record to a model that continuously drives and adapts revenue execution. Our platform captures deal data signals, and uses tailor-built AI to create the right context and drive action across sales teams. Instead of disconnected insights and siloed workflows, sales teams operate with shared understanding, faster decisions, and execution that stays aligned to the business. Trusted by thousands of enterprises including Adobe, 3M, IBM, and Zoom, Clari + Salesloft powers the forecast, surfaces pipeline risk, and drives proactive execution—returning thousands of hours to the field and enabling predictable, scalable growth. **Average Rating:** 4.5/5.0 **Total Reviews:** 4,153 **How Do G2 Users Rate Salesloft?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) **Who Is the Company Behind Salesloft?** - **Seller:** [Salesloft](https://www.g2.com/sellers/salesloft) - **Company Website:** https://salesloft.com - **Year Founded:** 2011 - **HQ Location:** Atlanta, GA - **Twitter:** @Salesloft (18,437 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2296178/ (1,097 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Account Executive, Sales Development Representative - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 56% Mid-Market, 23% Small-Business #### What Are Salesloft's Pros and Cons? **Pros:** - Ease of Use (256 reviews) - Integrations (211 reviews) - Email Tracking (201 reviews) - Easy Tracking (165 reviews) - Helpful (158 reviews) **Cons:** - Call Issues (164 reviews) - Integration Issues (134 reviews) - Learning Curve (116 reviews) - Limited Features (114 reviews) - Missing Features (95 reviews) ### What Do G2 Reviewers Say About Salesloft? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Salesloft, enhancing their daily selling experience with a simple, organized interface. - Users value the **seamless integration** with Salesforce, enhancing outreach efficiency and organization across teams. - Users appreciate the **email tracking features** for easily measuring open rates and managing tasks efficiently. - Users appreciate the **easy tracking** features of Salesloft, enhancing their efficiency in managing outreach campaigns. - Users find Salesloft **extremely helpful** in managing pipelines and measuring engagement through open rates and templates. **Cons:** - Users experience **call issues** with Salesloft, finding the app misaligned during calls and support inconsistent. - Users experience **integration issues** with Salesloft, particularly with HubSpot and other platforms, affecting efficiency. - Users find the **learning curve steep** , making initial use of Salesloft challenging and somewhat overwhelming. - Users highlight the **limited features** of Salesloft, expressing a desire for enhanced integrations and customization options. - Users feel Salesloft is missing **key features** like an auto-dialer and domain rotation, hindering productivity and email deliverability. #### What Are Recent G2 Reviews of Salesloft? **"[Easy-to-Use Cadences and Automation That Boost SDR Efficiency](https://www.g2.com/survey_responses/salesloft-review-12625459)"** **Rating:** 4.5/5.0 stars *— Verified User in Computer Software* [Read full review](https://www.g2.com/survey_responses/salesloft-review-12625459) --- **"[Boosts Sales Execution with Structured Cadences and CRM-Integrated Insights](https://www.g2.com/survey_responses/salesloft-review-12628860)"** **Rating:** 4.0/5.0 stars *— Harrison P.* [Read full review](https://www.g2.com/survey_responses/salesloft-review-12628860) --- #### What Are G2 Users Discussing About Salesloft? - [What innovative strategies are sales teams adopting with Salesloft to enhance customer engagement and sales effectiveness?](https://www.g2.com/discussions/what-innovative-strategies-are-sales-teams-adopting-with-salesloft-to-enhance-customer-engagement-and-sales-effectiveness) - [How is Salesloft being used to enhance operational efficiency and user experience in its specific field?](https://www.g2.com/discussions/how-is-salesloft-being-used-to-enhance-operational-efficiency-and-user-experience-in-its-specific-field) - 1 comment - [What is Salesloft used for?](https://www.g2.com/discussions/salesloft-what-is-salesloft-used-for) - 1 comment - [How much does SalesLoft cost?](https://www.g2.com/discussions/how-much-does-salesloft-cost) - [Is SalesLoft a CRM?](https://www.g2.com/discussions/is-salesloft-a-crm) - 6 comments, 1 upvote ### 18. [Alteryx](https://www.g2.com/products/alteryx/reviews) Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. **Average Rating:** 4.6/5.0 **Total Reviews:** 851 **How Do G2 Users Rate Alteryx?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) - **AI Text Summarization:** 7.2/10 (Category avg: 8.1/10) - **Algorithms:** 8.3/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.0/10 (Category avg: 8.1/10) **Who Is the Company Behind Alteryx?** - **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx) - **Company Website:** https://www.alteryx.com - **Year Founded:** 1997 - **HQ Location:** Irvine, CA - **Twitter:** @alteryx (26,149 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,304 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Analyst - **Top Industries:** Financial Services, Accounting - **Company Size:** 63% Enterprise, 21% Mid-Market #### What Are Alteryx's Pros and Cons? **Pros:** - Ease of Use (333 reviews) - Automation (148 reviews) - Intuitive (132 reviews) - Easy Learning (102 reviews) - Efficiency (102 reviews) **Cons:** - Expensive (88 reviews) - Learning Curve (80 reviews) - Missing Features (62 reviews) - Learning Difficulty (55 reviews) - Slow Performance (41 reviews) ### What Do G2 Reviewers Say About Alteryx? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Alteryx, finding it user-friendly and efficient for non-technical users. - Users appreciate the **automation capabilities** of Alteryx, enhancing speed and efficiency in data preparation and analysis. - Users love the **intuitive design** of Alteryx, making data management and workflow creation effortless and efficient. - Users find Alteryx to be **very easy to learn and use** , enhancing their data workflow and automation experience. - Users appreciate the **efficiency** of Alteryx, enabling quick data processing and streamlined workflows without complex coding. **Cons:** - Users mention that Alteryx has a **high cost** which can be challenging for small teams and startups. - Users find a **steep learning curve** for advanced features, making it challenging for beginners to master Alteryx quickly. - Users point out the **missing features** in Alteryx, such as limited connectors and issues with output flexibility. - Users find **learning difficulty** in Alteryx due to confusing tools and troubleshooting errors, especially for beginners. - Users encounter **slow performance** when processing large datasets, impacting efficiency and usability in Alteryx. #### What Are Recent G2 Reviews of Alteryx? **"[Powerful, Time-Saving Data Prep But Pricey, Windows-Only, and Weak on Reporting](https://www.g2.com/survey_responses/alteryx-review-12999843)"** **Rating:** 4.5/5.0 stars *— jayesh l.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-12999843) --- **"[Intuitive Drag-and-Drop Analytics That Speeds Up Data Prep and Insights](https://www.g2.com/survey_responses/alteryx-review-12983224)"** **Rating:** 4.5/5.0 stars *— Akhil S.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-12983224) --- ### 19. [DataRobot](https://www.g2.com/products/datarobot/reviews) DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models. This platform maximizes business value by delivering AI at scale and continuously optimizing performance over time. The company’s proven combination of cutting edge software and world-class AI implementation, training, and support services, empowers any organization – regardless of size, industry, or resources – to drive better business outcomes with AI. **Average Rating:** 4.4/5.0 **Total Reviews:** 28 **How Do G2 Users Rate DataRobot?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) **Who Is the Company Behind DataRobot?** - **Seller:** [DataRobot](https://www.g2.com/sellers/datarobot) - **Year Founded:** 2012 - **HQ Location:** Boston, Massachusetts - **Twitter:** @DataRobot (19,225 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2672915/ (883 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software - **Company Size:** 52% Small-Business, 31% Mid-Market #### What Are Recent G2 Reviews of DataRobot? **"[Fast, Insightful Automated Modeling with DataRobot](https://www.g2.com/survey_responses/datarobot-review-11788506)"** **Rating:** 4.5/5.0 stars *— Verified User in Financial Services* [Read full review](https://www.g2.com/survey_responses/datarobot-review-11788506) --- **"[Streamlined AutoML with Quick Deployment](https://www.g2.com/survey_responses/datarobot-review-13119818)"** **Rating:** 4.5/5.0 stars *— Verified User* [Read full review](https://www.g2.com/survey_responses/datarobot-review-13119818) --- ### 20. [Demandbase One](https://www.g2.com/products/demandbase-one/reviews) Demandbase is the leading, enterprise-grade account-based GTM platform for sales and marketing teams designed to make every moment and every dollar count. Since creating the category in 2013, we have been pioneering technologies to sharpen revenue teams’ ability to confidently deliver the right message to the right customers at the right time. Powered by industry-leading data, our transparent and tunable AI-enhanced model, and integrations that meet your tech stack where it is, Demandbase helps you to take meaningful action confidently and efficiently. We know that there’s no such thing as ‘one-size- fits-all’ account-based marketing and sales. That’s why we built our platform to be flexible, easily handling dynamic GTM motions, nuanced business rules, and diverse integrations that others struggle with. Demandbase One™ is your account-based GTM command center, powering your entire revenue stack. Our AI-driven engine unifies first and third-party data, streamlines cross-channel execution, and connects the tools in your stack with the same data, insights, and workflows to accelerate your revenue. **Average Rating:** 4.4/5.0 **Total Reviews:** 1,941 **How Do G2 Users Rate Demandbase One?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) **Who Is the Company Behind Demandbase One?** - **Seller:** [Demandbase](https://www.g2.com/sellers/demandbase) - **Company Website:** https://www.demandbase.com - **Year Founded:** 2005 - **HQ Location:** San Francisco, CA - **Twitter:** @Demandbase (21,346 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/89759/ (987 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Account Executive, Business Development Representative - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 48% Mid-Market, 32% Enterprise #### What Are Demandbase One's Pros and Cons? **Pros:** - Ease of Use (225 reviews) - Lead Generation (201 reviews) - Insights (184 reviews) - Features (173 reviews) - Intent Data (170 reviews) **Cons:** - Learning Curve (86 reviews) - Steep Learning Curve (77 reviews) - Complexity (70 reviews) - Learning Difficulty (63 reviews) - Not Intuitive (63 reviews) ### What Do G2 Reviewers Say About Demandbase One? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of Demandbase One, enhancing efficiency in building targeted custom audiences effortlessly. - Users value the **comprehensive datasets** of Demandbase One, enhancing targeted marketing and audience engagement strategies. - Users value the **comprehensive toolset** of Demandbase One, enhancing account targeting and analytics for effective ABM strategy. - Users value the **unified data and seamless integrations** of Demandbase One, enhancing their marketing and sales efforts significantly. - Users value the **insightful intent data** from Demandbase One for fast and effective account targeting and decision making. **Cons:** - Users face a **steep learning curve** with Demandbase One, making it challenging to utilize all features effectively. - Users find the **steep learning curve** of Demandbase One frustrating, requiring more training to maximize its features. - Users find the **steep learning curve** of Demandbase One challenging, particularly for new or smaller teams lacking expertise. - Users find the **learning difficulty** of Demandbase One challenging, particularly for those lacking technical skills. - Users find the **navigation unintuitive** , making it challenging to navigate and manage campaigns effectively. #### What Are Recent G2 Reviews of Demandbase One? **"[Demandbase One: Powerful Targeting, Intent Insights, and Account-Level Visibility](https://www.g2.com/survey_responses/demandbase-one-review-12742698)"** **Rating:** 4.0/5.0 stars *— Nijat I.* [Read full review](https://www.g2.com/survey_responses/demandbase-one-review-12742698) --- **"[Powerful Intent Data and Account Insights for B2B Account Prioritization](https://www.g2.com/survey_responses/demandbase-one-review-12823589)"** **Rating:** 4.5/5.0 stars *— Himanshu J.* [Read full review](https://www.g2.com/survey_responses/demandbase-one-review-12823589) --- #### What Are G2 Users Discussing About Demandbase One? - [As a beginner, how do I effectively use Demandbase One's account-based marketing feature for targeted campaigns?](https://www.g2.com/discussions/as-a-beginner-how-do-i-effectively-use-demandbase-one-s-account-based-marketing-feature-for-targeted-campaigns) - 1 upvote - [What is Demandbase ABM/ABX Cloud used for?](https://www.g2.com/discussions/what-is-demandbase-abm-abx-cloud-used-for) - [What does Insideview Data Integrity do?](https://www.g2.com/discussions/what-does-insideview-data-integrity-do) - [What is the use of Insideview Data Integrity?](https://www.g2.com/discussions/what-is-the-use-of-insideview-data-integrity) - [What does inside view do?](https://www.g2.com/discussions/what-does-inside-view-do) ### 21. [JMP](https://www.g2.com/products/jmp/reviews) JMP, data analysis software for Mac and Windows, combines the strength of interactive visualization with powerful statistics. Importing and processing data is easy. The drag-and-drop interface, dynamically linked graphs, libraries of advanced analytic functionality, scripting language and ways of sharing findings with others, allows users to dig deeply into their data, with greater ease and speed. Originally developed in the 1980’s to capture the new value in GUI for personal computers, JMP remains dedicated to adding cutting-edge statistical methods and special analysis techniques from a variety of industries to the software’s functionality with each release. The organization's founder, John Sall, still serves as Chief Architect. To see a full list of data connectors please visit https://www.jmp.com/en/software/analytic-workflow/data-connectors **Average Rating:** 4.5/5.0 **Total Reviews:** 206 **How Do G2 Users Rate JMP?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) - **AI Text Summarization:** 10.0/10 (Category avg: 8.1/10) - **Algorithms:** 8.7/10 (Category avg: 8.5/10) - **AI Text Generation:** 10.0/10 (Category avg: 8.1/10) **Who Is the Company Behind JMP?** - **Seller:** [JMP Statistical Discovery](https://www.g2.com/sellers/jmp-statistical-discovery) - **Company Website:** https://www.jmp.com - **Year Founded:** 1989 - **HQ Location:** Cary, North Carolina - **Twitter:** @JMP_software (2,760 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/jmp/ (1,031 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Student - **Top Industries:** Higher Education, Information Technology and Services - **Company Size:** 42% Enterprise, 33% Small-Business #### What Are JMP's Pros and Cons? **Pros:** - Ease of Use (10 reviews) - Data Visualization (9 reviews) - Statistical Analysis (5 reviews) - Visualization (5 reviews) - User Interface (4 reviews) **Cons:** - Expensive (6 reviews) - Learning Curve (4 reviews) - Limited Flexibility (4 reviews) - Learning Difficulty (3 reviews) - Limitations in Storage (2 reviews) ### What Do G2 Reviewers Say About JMP? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of JMP, allowing for simple data exploration and visualization without complicated coding. - Users love the **easy and interactive data visualization** in JMP, making pattern recognition and analysis simple and efficient. - Users appreciate the **ease of statistical analysis** in JMP, enabling seamless data exploration and trend visualization. - Users praise JMP for its **easy data visualization** , allowing intuitive exploration and clear presentation of trends. - Users appreciate the **intuitive and interactive interface** of JMP, enhancing data analysis and visualization experiences seamlessly. **Cons:** - Users find JMP **expensive** , making it challenging for smaller users to justify its cost compared to alternatives. - Users note a significant **learning curve** with JMP, making it challenging for beginners to navigate effectively. - Users feel a **limited flexibility** in JMP, especially regarding integration and available models for analysis. - Users find the **learning difficulty** significant due to an overwhelming interface and a steep learning curve for advanced features. - Users find **limitations in storage** and model availability in JMP, hindering their multivariate analysis efforts. #### What Are Recent G2 Reviews of JMP? **"[JMP Software: Good Tool, Few Downsides](https://www.g2.com/survey_responses/jmp-review-11188568)"** **Rating:** 4.0/5.0 stars *— Verified User in Pharmaceuticals* [Read full review](https://www.g2.com/survey_responses/jmp-review-11188568) --- **"[Intuitive Visual Analytics, Powerful Tools—But Resource-Heavy and Pricey](https://www.g2.com/survey_responses/jmp-review-11859383)"** **Rating:** 4.5/5.0 stars *— Ganesh W.* [Read full review](https://www.g2.com/survey_responses/jmp-review-11859383) --- #### What Are G2 Users Discussing About JMP? - [What is JMP used for?](https://www.g2.com/discussions/what-is-jmp-used-for) - 1 comment - [Who uses JMP?](https://www.g2.com/discussions/who-uses-jmp) - 3 comments - [Is JMP software validated?](https://www.g2.com/discussions/is-jmp-software-validated) - 1 comment - [What is the difference between JMP and JMP Pro?](https://www.g2.com/discussions/what-is-the-difference-between-jmp-and-jmp-pro) - [What is JMP software used for?](https://www.g2.com/discussions/what-is-jmp-software-used-for) - 1 comment ### 22. [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) IBM Watson Studio on IBM Cloud Pak for Data is a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation. It allows businesses to scale trustworthy AI and optimize decisions. Build, run, and manage AI models on any cloud through an automated end-to-end AI lifecycle--simplifying experimentation and deployment, speeding up data exploration and preparation, and improving model development and training. Govern and monitor models to mitigate drift and bias, and manage model risk. Build a ModelOps practice that synchronizes application and model pipelines to operationalize responsible, explainable AI across your enterprise. As a key offering of IBM Cloud Pak for Data, a unified data and AI platform, Watson Studio integrates seamlessly with data management services, data privacy and security capabilities, AI application tooling, open source frameworks, and a robust technology ecosystem. It unites teams and empowers businesses to build the modern information architecture that AI requires and infuse it across the organization. IBM Watson Studio is code-optional, allowing both data scientists and business analysts to work on the same platform by providing the best of open source tools along with visual, drag-and-drop capabilities. It enables organizations to tap into data assets and inject predictions into business processes and modern applications—helping them maximize their business value. It's suited for hybrid multicloud environments that demand mission-critical performance, security, and governance. Features include: • AutoAI that eliminates time-consuming, repetitive tasks by automating data preparation, model development, feature engineering and hyperparameter optimization. • Text Analytics for uncovering insights from unstructured data • Drag-and-drop visual model-building with SPSS Modeler • Broad data access – flat files, spreadsheets, major relational databases • Sophisticated graphics engine for building stunning visualizations • Support for Python 3 Notebooks Watson Studio is available via several deployment options: • IBM Cloud Pak for Data – An open, extensible data and AI platform that runs on any cloud • IBM Cloud Pak for Data System – A hybrid cloud, on-premises platform-in-a-box • IBM Cloud Pak for Data as a Service – A set of IBM Cloud Pak for Data platform services fully managed on the IBM Cloud **Average Rating:** 4.2/5.0 **Total Reviews:** 163 **How Do G2 Users Rate IBM Watson Studio?** - **Has the product been a good partner in doing business?:** 8.0/10 (Category avg: 8.9/10) - **AI Text Summarization:** 8.3/10 (Category avg: 8.1/10) - **Algorithms:** 8.1/10 (Category avg: 8.5/10) - **AI Text Generation:** 9.3/10 (Category avg: 8.1/10) **Who Is the Company Behind IBM Watson Studio?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Who Uses This:** Software Engineer, CEO - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 49% Enterprise, 31% Small-Business #### What Are IBM Watson Studio's Pros and Cons? **Pros:** - AI Capabilities (4 reviews) - AI Technology (4 reviews) - Ease of Use (4 reviews) - Machine Learning (4 reviews) - AI Integration (3 reviews) **Cons:** - Expensive (3 reviews) - Learning Curve (3 reviews) - Steep Learning Curve (3 reviews) - Complex Interface (1 reviews) - Complexity (1 reviews) ### What Do G2 Reviewers Say About IBM Watson Studio? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **Auto AI capability** of IBM Watson Studio, which automates tasks and enhances data science efficiency. - Users appreciate the **Auto AI capability** of IBM Watson Studio, significantly reducing manual work and enhancing productivity. - Users value the **ease of use** of IBM Watson Studio, enabling quick project initiation and seamless collaboration. - Users appreciate the **Auto AI capability** of IBM Watson Studio, significantly reducing manual work in data preprocessing. - Users find the **easy AI integration** of IBM Watson Studio transformative, enhancing their data science and ML workflows significantly. **Cons:** - Users find the **expensive pricing** of IBM Watson Studio to be a significant barrier, especially for individuals and startups. - Users find the **steep learning curve** of IBM Watson Studio challenging, especially for beginners navigating complex features. - Users face a **steep learning curve** with IBM Watson Studio, making it challenging for beginners to navigate the complex features. - Users find the **complex interface** of IBM Watson Studio challenging, especially for beginners navigating its features. - Users find the **steep learning curve** of IBM Watson Studio challenging, particularly due to its complex interface. #### What Are Recent G2 Reviews of IBM Watson Studio? **"[An all-in-one platform useful for data analysis and AI](https://www.g2.com/survey_responses/ibm-watson-studio-review-13090033)"** **Rating:** 4.5/5.0 stars *— Miguel P.* [Read full review](https://www.g2.com/survey_responses/ibm-watson-studio-review-13090033) --- **"[Robust Platform for Seamless Data Science Collaboration](https://www.g2.com/survey_responses/ibm-watson-studio-review-12313951)"** **Rating:** 4.5/5.0 stars *— Naimish M.* [Read full review](https://www.g2.com/survey_responses/ibm-watson-studio-review-12313951) --- #### What Are G2 Users Discussing About IBM Watson Studio? - [What is IBM Watson Studio used for?](https://www.g2.com/discussions/what-is-ibm-watson-studio-used-for) - 1 upvote - [What are the main benefits of using AutoAI in IBM Watson Studio?](https://www.g2.com/discussions/what-are-the-main-benefits-of-using-autoai-in-ibm-watson-studio) - [Is IBM Watson Studio free?](https://www.g2.com/discussions/is-ibm-watson-studio-free) - [How do I use IBM Watson Studio?](https://www.g2.com/discussions/how-do-i-use-ibm-watson-studio) - [What does IBM Watson Studio do?](https://www.g2.com/discussions/what-does-ibm-watson-studio-do) ### 23. [Domo](https://www.g2.com/products/domo/reviews) Domo's AI and Data Products Platform empowers organizations to turn data into actionable insights and solutions. It allows users to seamlessly connect diverse data sources, prepare data for use, and generate dynamic reports and visualizations—all within a single interface. With built-in AI and automation capabilities, teams can easily build and use AI agents, streamline workflows, and create tailored solutions. **Average Rating:** 4.3/5.0 **Total Reviews:** 1,030 **How Do G2 Users Rate Domo?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) **Who Is the Company Behind Domo?** - **Seller:** [Domo](https://www.g2.com/sellers/domo) - **Company Website:** https://www.domo.com - **Year Founded:** 2010 - **HQ Location:** American Fork, UT - **Twitter:** @Domotalk (63,513 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/25237/ (1,299 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Business Analyst - **Top Industries:** Computer Software, Marketing and Advertising - **Company Size:** 49% Mid-Market, 29% Enterprise #### What Are Domo's Pros and Cons? **Pros:** - Ease of Use (248 reviews) - Data Visualization (116 reviews) - Intuitive (95 reviews) - Easy Integrations (93 reviews) - Integrations (88 reviews) **Cons:** - Learning Curve (66 reviews) - Missing Features (59 reviews) - Data Management Issues (55 reviews) - Expensive (45 reviews) - Complexity (43 reviews) ### What Do G2 Reviewers Say About Domo? *AI-generated summary from verified user reviews* **Pros:** - Users value Domo's **ease of use** , making it accessible for all, even those who aren't tech-savvy. - Users value the **flexible dashboards** in Domo, allowing seamless data visualization from various sources. - Users find Domo's **intuitive design** enhances data handling and decision-making, making it accessible for all skill levels. - Users praise Domo for its **easy integrations** , enabling seamless data connections and enhancing data management efficiency. - Users value the **seamless integration** capabilities of Domo, enhancing data management across various platforms and sources. **Cons:** - Users find the **learning curve challenging** with Domo, often requiring dedicated resources to manage updates and functionalities. - Users struggle with **missing features** in Domo, including outdated systems and limited capabilities in visualizations and connectors. - Users are frustrated by **data management issues** , including upload adjustments and poor organization of datasets in Domo. - Users find Domo to be **expensive** due to high costs associated with features and external consulting needs. - Users find Domo's **complexity** overwhelming, requiring technical expertise and extensive setup that complicate the user experience. #### What Are Recent G2 Reviews of Domo? **"[Domo Turns Disconnected Reports Into a Game-Changing Sales Scorecard](https://www.g2.com/survey_responses/domo-review-13128007)"** **Rating:** 5.0/5.0 stars *— Renee G.* [Read full review](https://www.g2.com/survey_responses/domo-review-13128007) --- **"[Fast, Reliable Dashboarding with Quick Data Connections in Domo](https://www.g2.com/survey_responses/domo-review-13150907)"** **Rating:** 4.5/5.0 stars *— Katie S.* [Read full review](https://www.g2.com/survey_responses/domo-review-13150907) --- #### What Are G2 Users Discussing About Domo? - [What is Domo used for?](https://www.g2.com/discussions/what-is-domo-used-for) - 1 comment - [How much does Domo cost?](https://www.g2.com/discussions/how-much-does-domo-cost) - [What is Domo data?](https://www.g2.com/discussions/what-is-domo-data) - [Is Domo any good?](https://www.g2.com/discussions/is-domo-any-good) - [What does Domo software do?](https://www.g2.com/discussions/what-does-domo-software-do) ### 24. [Plotly Dash Enterprise](https://www.g2.com/products/plotly-dash-enterprise/reviews) Dash is the trusted solution for operationalizing Python models, allowing data science teams to focus on data and models, while still producing and deploying enterprise-ready apps. What would typically require a team of back-end developers, front-end developers and IT can all be done with Dash. It enables data science teams to build, design, deploy, and securely manage data-driven applications that align with your business goals. Companies can deliver on their data, analytic, and AI initiatives quickly and effectively -- no JavaScript, CSS, CronJobs or DevOps required. **Average Rating:** 4.8/5.0 **Total Reviews:** 36 **How Do G2 Users Rate Plotly Dash Enterprise?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) - **Algorithms:** 9.2/10 (Category avg: 8.5/10) **Who Is the Company Behind Plotly Dash Enterprise?** - **Seller:** [Plotly](https://www.g2.com/sellers/plotly) - **Year Founded:** 2013 - **HQ Location:** Montréal, CA - **Twitter:** @plotlygraphs (41,308 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3327684/ (105 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software - **Company Size:** 47% Small-Business, 31% Enterprise #### What Are Plotly Dash Enterprise's Pros and Cons? **Pros:** - Charting Features (1 reviews) - Coding Ease (1 reviews) - Customer Support (1 reviews) - Dashboard Management (1 reviews) - Data Visualization (1 reviews) ### What Do G2 Reviewers Say About Plotly Dash Enterprise? *AI-generated summary from verified user reviews* **Pros:** - Users love the **ease of creating beautiful visualizations** with Drag-and-Drop features in Plotly Dash Enterprise. - Users love the **coding ease** of Plotly Dash Enterprise, allowing simple chart creation through drag and drop functionality. - Users value the **customer support** of Plotly Dash Enterprise, enhancing their experience with prompt and effective assistance. - Users love the **intuitive dashboard management** of Plotly Dash Enterprise, enhancing efficiency with easy visualizations and SQL support. - Users value the **ease of creating stunning visualizations** in Plotly Dash Enterprise, enhancing their data presentation experience. #### What Are Recent G2 Reviews of Plotly Dash Enterprise? **"[Its the perfect Data Management](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-10698270)"** **Rating:** 4.5/5.0 stars *— Maria F.* [Read full review](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-10698270) --- **"[Dash Dominance in Creating Interactive Web Apps for Your Data Insights](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-8889756)"** **Rating:** 5.0/5.0 stars *— Uttam M.* [Read full review](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-8889756) --- #### What Are G2 Users Discussing About Plotly Dash Enterprise? - [What are 3 benefits of a dashboard?](https://www.g2.com/discussions/dash-what-are-3-benefits-of-a-dashboard) - [What is the best dashboard software?](https://www.g2.com/discussions/dash-what-is-the-best-dashboard-software) - [How good is Dash?](https://www.g2.com/discussions/how-good-is-dash) - [What is the function of a dashboard?](https://www.g2.com/discussions/what-is-the-function-of-a-dashboard) ### 25. [SAS Enterprise Miner](https://www.g2.com/products/sas-enterprise-miner/reviews) SAS Enterprise Miner is a comprehensive data mining and predictive analytics software designed to streamline the process of developing descriptive and predictive models. It enables users to analyze vast amounts of data efficiently, uncovering patterns and relationships that inform better decision-making. With an intuitive graphical user interface, SAS Enterprise Miner facilitates the entire data mining process, from data preparation to model assessment, making advanced analytics accessible to both technical and non-technical users. Key Features and Functionality: - User-Friendly Interface: An interactive GUI allows users to build process flow diagrams, simplifying the modeling process. - Advanced Data Preparation: Tools for handling missing values, filtering outliers, and performing data transformations enhance data quality. - Diverse Modeling Techniques: Supports a wide range of algorithms, including decision trees, neural networks, and regression models, catering to various analytical needs. - Open Source Integration: Seamless integration with R enables users to perform data transformations and model training within the platform. - High-Performance Capabilities: Incorporates high-performance data mining nodes to boost processing efficiency. - Automated Scoring: Generates score code in multiple languages (SAS, C, Java, PMML) for deployment across various environments. - Model Comparison and Management: Features for comparing multiple models using lift curves and statistical diagnostics to identify the best-performing models. Primary Value and Solutions Provided: SAS Enterprise Miner empowers organizations to harness the full potential of their data by providing a robust platform for developing accurate predictive models. It addresses challenges such as fraud detection, risk minimization, resource demand forecasting, and customer attrition reduction. By automating and simplifying complex data mining tasks, it enables users to make informed, data-driven decisions, ultimately enhancing operational efficiency and competitive advantage. **Average Rating:** 4.2/5.0 **Total Reviews:** 185 **How Do G2 Users Rate SAS Enterprise Miner?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **AI Text Summarization:** 7.4/10 (Category avg: 8.1/10) - **Algorithms:** 8.0/10 (Category avg: 8.5/10) - **AI Text Generation:** 7.4/10 (Category avg: 8.1/10) **Who Is the Company Behind SAS Enterprise Miner?** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,863 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,638 employees on LinkedIn®) - **Phone:** 1-800-727-0025 **Who Uses This Product?** - **Top Industries:** Higher Education, Information Technology and Services - **Company Size:** 60% Enterprise, 28% Mid-Market #### What Are SAS Enterprise Miner's Pros and Cons? **Pros:** - Ease of Installation (1 reviews) - Ease of Use (1 reviews) - Statistical Analysis (1 reviews) **Cons:** - Learning Curve (1 reviews) - Not User-Friendly (1 reviews) - Steep Learning Curve (1 reviews) ### What Do G2 Reviewers Say About SAS Enterprise Miner? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of installation** with SAS Enterprise Miner, simplifying the setup for node-based analysis. - Users appreciate the **ease of creating node-based analyses** in SAS Enterprise Miner, enhancing their analytical workflows. - Users value the **ease of creating node-based analyses** in SAS Enterprise Miner, enhancing their analytical experience. **Cons:** - Users find **the learning curve steep** , especially when generating output for other SAS products as beginners. - Users find that generating output from SAS Enterprise Miner can be **challenging for inexperienced users** , impacting usability. - Users find the **steep learning curve** of SAS Enterprise Miner daunting, particularly when generating output to other products. #### What Are Recent G2 Reviews of SAS Enterprise Miner? **"[Great Decision Trees That Deliver](https://www.g2.com/survey_responses/sas-enterprise-miner-review-12697539)"** **Rating:** 4.5/5.0 stars *— Rohan K.* [Read full review](https://www.g2.com/survey_responses/sas-enterprise-miner-review-12697539) --- **"[Excellent product for statistical analysis](https://www.g2.com/survey_responses/sas-enterprise-miner-review-11134264)"** **Rating:** 5.0/5.0 stars *— bobby x.* [Read full review](https://www.g2.com/survey_responses/sas-enterprise-miner-review-11134264) --- #### What Are G2 Users Discussing About SAS Enterprise Miner? - [Is SAS software dying?](https://www.g2.com/discussions/sas-advanced-analytics-is-sas-software-dying) - [Who uses SAS Enterprise Miner?](https://www.g2.com/discussions/who-uses-sas-enterprise-miner) - [What is SAS software used for?](https://www.g2.com/discussions/sas-advanced-analytics-what-is-sas-software-used-for) - [Is SAS Enterprise Miner useful?](https://www.g2.com/discussions/is-sas-enterprise-miner-useful) - [What is advanced analytics platform?](https://www.g2.com/discussions/what-is-advanced-analytics-platform) - 1 comment ## What Is Predictive Analytics Software? [Analytics Tools & Software](https://www.g2.com/categories/analytics-tools-software) ## What Software Categories Are Similar to Predictive Analytics Software? - [Data Visualization Tools](https://www.g2.com/categories/data-visualization-tools) - [Analytics Platforms](https://www.g2.com/categories/analytics-platforms) - [Embedded Business Intelligence Software](https://www.g2.com/categories/embedded-business-intelligence) - [Machine Learning Software](https://www.g2.com/categories/machine-learning) - [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) - [Statistical Analysis Software](https://www.g2.com/categories/statistical-analysis) - [Time Series Intelligence Software](https://www.g2.com/categories/time-series-intelligence) --- ## How Do You Choose the Right Predictive Analytics Software? ### What You Should Know About Predictive Analytics Software ### What are predictive analytics tools and software? Predictive analytics software is all about making business outcomes predictable. Data scientists and data analysts can do this by using data mining and predictive modeling to analyze historical data. By better understanding the past, businesses can gain insights into the future. [Predictive analytics](https://www.g2.com/articles/predictive-analytics) is a step further than general [business intelligence](https://www.g2.com/glossary/business-intelligence-definition), which companies use to pull actionable insights from their data sets. Instead, users can develop [machine learning algorithms](https://www.g2.com/articles/what-is-machine-learning) and predictive models to help forecast and achieve business-critical numbers. The reason businesses can hit those critical numbers and become more predictive is due to the boom of big data. Companies can harness their data like never before. By recording and owning more and more historical and real-time data, data scientists have larger sample sizes to work with, meaning they can be much more accurate. Additionally, companies investing in predictive analytics without ensuring that their data is accurate, clean, and accessible will ultimately be wasting their time. However, those who can wrangle their data properly will create a significant competitive edge and hold an advantage in the market. ### Benefits of using predictive analytics tools - Accurately predict and forecast revenue numbers based on a wide range of variables - Understand and account for customer churn and retention - Predict employee churn based on historical factors for turnover - Make more precise, data-driven decisions in all departments based on available data - Determine both risks and opportunities that were otherwise hidden within company data ### Why use predictive analytics solutions? There are a number of applications for predictive analytics software and reasons businesses should adopt them, but they all boil down to understanding what has happened in the past, what could happen in the future, and what should be done to ensure positive business outcomes. These are considered [descriptive analytics, predictive analytics, and prescriptive analytics](https://www.g2.com/articles/types-of-data-analytics). **Descriptive Analytics (understanding the past) —** Descriptive analytics deals with understanding what has happened in the past and how it has influenced where a business is in the present. This means undergoing data mining on a company’s historical data. This type of analysis can be obtained by using business intelligence tools, big data analytics, or time-series data. Regardless of how it is attained, providing descriptive analytics is a key foundation of predictive analytics and creating data-driven decision-making processes. It requires thorough data preparation and organizing the data for easy descriptive analysis. **Predictive Analytics (knowing what is possible) —** Predictive analytics allows users and businesses to know and anticipate potential outcomes. Building predictive models based on descriptive analysis can ensure that businesses do not make the same mistake twice. It can also provide more accurate forecasting and planning, which helps to optimize efficiency. Ultimately, this analysis makes the unknown known. **Prescriptive Analytics (so now what?) —** The final step and ultimate reason for using predictive analytics tools is to make clear actions based on the suggestions and recommendations of the predictive models. This is where machine learning and deep learning functionality come into play. Some predictive analytics solutions can provide actionable insights without human intervention. For example, it can provide a short list of sales accounts that should close quickly based on several variables. Becoming prescriptive takes analytics a step further and is the ultimate reason for adopting advanced, predictive analytics. ### Who uses predictive analytics platforms? To fully take advantage of predictive analytics platforms, businesses need to hire highly skilled data scientists with knowledge in machine learning development and predictive modeling. These skilled workers are not abundant, so they are often paid very well. Dedicating financial resources to these positions may not be an option for every company, but those who can afford data scientists have a leg up on the competition. While data scientists or data analysts are the employees tasked with using predictive analytics software, there are many industries and departments that can be impacted by using predictive analytics: **Manufacturing and Supply Chain—** One area that can be greatly enhanced by using predictive analysis is demand planning for manufacturing companies. With more accurate forecasting, businesses can avoid risks like shortages and surpluses. Additionally, companies can become predictive about quality management and production issues. By analyzing what has caused production failures in the past, companies can anticipate and avoid production breakdowns in the future. Distribution is another major aspect of the supply chain that can be further optimized with predictive modeling. By better estimating where goods will need to be delivered and the risks that may hold up distribution modes, businesses can provide better service and more efficiently deliver their products to customers. Taking into account historical data, such as weather, traffic, and accident records, shipping can become a more precise science. **Retail —** Retail is another industry that is ripe for optimization with the help of predictive analytics. Retail predictive analytics can provide businesses with insights on everything from pricing optimization to understanding how shoppers navigate brick-and-mortar stores for better in-store organization of merchandise. E-commerce businesses can track these factors in a much more efficient manner. All e-commerce interactions can be recorded into a database and influenced by predictive models. This is one of the main reasons Amazon has been so successful and disruptive to brick-and-mortar retailers. Every decision can be made predictive with the help of data. **Marketing and Sales —** Being able to predict the actions of customers and prospects is an invaluable service for any business. Marketing teams can leverage predictive analytics software to project how marketing campaigns may perform, which segment of prospects to target with ads, and the potential conversion rates of each campaign. Understanding how these efforts impact the bottom line is critical to the success of marketing teams and translates into a much more efficient and productive sales team. At the same time, sales teams can leverage predictive modeling in such areas as lead scoring, determining which accounts to target first because they have a higher chance of closing. Ensuring that sales representatives are working smarter instead of harder means more revenue. A few [CRM](https://www.g2.com/categories/crm) and [marketing automation solutions](https://www.g2.com/categories/marketing-automation) provide some level of predictive functionality, but data scientists can separately funnel that data into dedicated predictive analytics tools to find cross-departmental correlations. **Financial Services—** The banking industry has long been ripe for disruption, but financial administrations are using predictive analytics solutions to better predict risk. Historical data can power predictive analytics software to predict fraudulent transactions and determine credit risks, among other functions. ### Types of predictive analytics software Predictive modeling is a complex science that requires years of training to understand. There is a reason data scientists are in high demand: not many people have a complete grasp of how to build predictive models. There are two main types of predictive models: classification and regression models. **Classification Models—** Simply put, classification puts a piece of data into a bucket or a class and labels it as such. Classification models essentially label data based on what an algorithm has already learned. The ultimate goal of classification models is to accurately bucket new data points into the proper classes so that the data can become predictive and prescriptive. **Regression Models—** Regression models analyze the relationship between two separate data points and help forecast what happens when they are placed side by side. For example, in baseball, teams may perform a regression analysis on the relationship between the number of fastballs thrown and the number of home runs hit. **Decision Trees —** One common type of classification model is a decision tree. These models predict several possible outcomes based on a variety of inputs. For example, if a sales team builds $1 million in a pipeline, they can close $100,000 in revenue, but if they create $10 million in a pipeline, they should be able to close $1 million in revenue. **Neural Networks—** Neural networks, known in the AI world as artificial neural networks, are extremely complex predictive models. These models can predict and analyze unstructured, nonlinear relationships between data points. These solutions provide pattern recognition and can help track anomalies. Artificial neural networks were originally created and built to mimic the synapses and neural aspects of the human brain. They are one of the contributing factors to the accelerated growth in artificial intelligence and deep learning. Other types of predictive modeling include Bayesian analysis, memory-based reasoning, k-nearest neighbor, support vector machines, and time-series data mining. ### Potential issues with predictive analytics software solutions **Lack of Skilled Employees—** The main issue with adopting predictive analytics software is the need for a skilled data scientist to interact with the data and build the models. There is a distinct skill gap in terms of finding users who understand how to pull data and build models and the implications that the data has on the overall business. For this reason, data scientists are in very high demand and, thus, expensive. **Data Organization—** Many companies face the challenge of organizing data so that it can be easily accessed. Harnessing big data sets that contain historical and real-time data is not easy in today's world. Companies often need to build a data warehouse or a data lake that can combine all the disparate data sources for easy access. This, again, requires highly knowledgeable employees. ### Software and services related to predictive analytics tools Predictive analytics software relates to many other analytics and [artificial intelligence software](https://www.g2.com/categories/artificial-intelligence) categories. [**Machine Learning Software**](https://www.g2.com/categories/machine-learning) **—** Machine learning algorithms are a key component of building effective predictive models. Many machine learning algorithms are built to provide recommendations or suggestions, which is also the end goal of predictive analytics software. Developers use these tools to embed machine learning inside applications, often to provide predictive and prescriptive analysis. [**Business Intelligence Platforms**](https://www.g2.com/categories/business-intelligence) **—** These tools are the traditional analytics solutions used to understand a company’s data. Data analysts use BI platforms to visualize and understand how specific actions impact business-critical initiatives. Some of these platforms offer predictive features, but their core purpose is not predictive modeling. [**Big Data Analytics**](https://www.g2.com/categories/big-data-analytics) **—** Big data analytics software, like business intelligence platforms, often provides predictive modeling functionality. However, these solutions are used more to track real-time data than to understand historical data. Big data analytics software connects to Hadoop or proprietary Hadoop distributions to better understand structured and unstructured data. These same data sources may be important for data scientists who are tasked with building predictive models.