# Best Analytics Platforms for Small Business *By [Tian Lin](https://research.g2.com/insights/author/tian-lin)* Products classified in the overall Analytics Platforms 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 Analytics Platforms 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 Analytics Platforms category. In addition to qualifying for inclusion in the Analytics Platforms category, to qualify for inclusion in the Small Business Analytics Platforms category, a product must have at least 10 reviews left by a reviewer from a small business. ## How Many Analytics Platforms Products Does G2 Track? **Total Products under this Category:** 338 ### Category Stats (Jun 2026) - **Average Rating**: 4.48/5 The average rating of products in this category, based on all submitted ratings - **New Reviews This Quarter**: 746 - **Buyer Segments**: Mid-Market 40% │ Enterprise 33% │ Small-Business 27% Represents the distribution of reviewers across all products in this category. - **Top Trending Product**: Bold Reports (+0.024) - Among all products in this category, Bold Reports recorded the largest rating increase compared to last month *Last updated: June 01, 2026* ## How Does G2 Rank Analytics Platforms Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 27,500+ Authentic Reviews - 338+ 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. ## Top Analytics Platforms at a Glance | # | Product | Rating | Best For | What Users Say | |---|---------|--------|----------|----------------| | 1 | [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) | 4.5/5.0 (1,576 reviews) | Microsoft-connected interactive dashboards | "[No-Code Microsoft Analytics with Easy Data Connections and Drag-and-Drop Dashboards](https://www.g2.com/survey_responses/microsoft-power-bi-review-12894515)" | | 2 | [Tableau](https://www.g2.com/products/tableau/reviews) | 4.4/5.0 (3,549 reviews) | Flexible visual dashboard exploration | "[Powerful, Flexible Visualizations with Minor Performance Delays](https://www.g2.com/survey_responses/tableau-review-11907092)" | | 3 | [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) | 4.3/5.0 (755 reviews) | Cloud analytics for governed data science | "[Powerful & Transforming Data into Decisions—Effortlessly and Intelligently.](https://www.g2.com/survey_responses/sas-viya-review-12682824)" | | 4 | [Alteryx](https://www.g2.com/products/alteryx/reviews) | 4.6/5.0 (774 reviews) | No-code data preparation and automation | "[Easy, Time-Saving Data Automation with Alteryx’s Drag-and-Drop Workflows](https://www.g2.com/survey_responses/alteryx-review-12594796)" | | 5 | [Databricks](https://www.g2.com/products/databricks/reviews) | 4.6/5.0 (761 reviews) | Governed lakehouse analytics and ML workflows | "[Databricks in my case: Multiple Integrations, Intuitive UI, and Reliable Performance](https://www.g2.com/survey_responses/databricks-review-12834055)" | | 6 | [Looker](https://www.g2.com/products/looker/reviews) | 4.4/5.0 (1,580 reviews) | Governed shared BI metrics | "[Transforms Data, But Challenging for Beginners](https://www.g2.com/survey_responses/looker-review-12784757)" | | 7 | [Domo](https://www.g2.com/products/domo/reviews) | 4.3/5.0 (987 reviews) | Centralized self-service business dashboards | "[All-in-One Platform for Real-Time Analytics and Dashboards](https://www.g2.com/survey_responses/domo-review-12676104)" | | 8 | [Kyvos Semantic Layer](https://www.g2.com/products/kyvos-semantic-layer/reviews) | 4.8/5.0 (252 reviews) | Semantic-layer acceleration for enterprise BI | "[Kyvos Unified Our Business Logic with a Single Semantic Model](https://www.g2.com/survey_responses/kyvos-semantic-layer-review-12797024)" | | 9 | [Sigma](https://www.g2.com/products/sigma-computing-sigma/reviews) | 4.4/5.0 (543 reviews) | Warehouse-native spreadsheet-style analytics | "[Easiest BI Tool: Live Snowflake Data in a Spreadsheet-Like Experience](https://www.g2.com/survey_responses/sigma-review-12573150)" | | 10 | [Hex](https://www.g2.com/products/hex-tech-hex/reviews) | 4.5/5.0 (392 reviews) | SQL and Python notebook analytics apps | "[Effortless Data Analysis with Powerful AI](https://www.g2.com/survey_responses/hex-review-12262172)" | ## Which Type of Analytics Platforms Tools Are You Looking For? - [Analytics Platforms](https://www.g2.com/categories/analytics-platforms) *(current)* - [Data Visualization Tools](https://www.g2.com/categories/data-visualization-tools) - [Predictive Analytics Software](https://www.g2.com/categories/predictive-analytics) - [Embedded Business Intelligence Software](https://www.g2.com/categories/embedded-business-intelligence) --- **Sponsored** ### Zoho Analytics Zoho Analytics is a GenAI-powered self-service BI and analytics platform that helps businesses collect, prepare, analyze, and present insights from their data, all within minutes. Integrate with 500+ native data sources, like files, feeds, local and cloud databases, cloud storage, and popular business apps. Clean, transform, enrich, and catalog data with our agentic AI-powered, self-service data preparation and management capabilities. Create and manage complex ETL data pipelines using our visual pipeline builder, process stream data for real-time analytics, and set up a strong metrics layer for quality analysis and management. Zoho Analytics comes with 100+ domain-specific prebuilt reports and dashboards, pre-trained NLQ models, intelligently modeled and blended data across business applications, and lots more. Use our intuitive drag-and-drop visualization builder to build insightful and interactive reports and dashboards using a wide variety of visual components, like charts, widgets, pivot tables, tabular views and more. Generate customized reports and dashboards using simple, natural language with our AI-powered conversational agent, Zia. Ask Zia goes beyond basic reporting; it enables users to perform diagnostic analytics, forecast key metrics, and receive intelligent insights and recommendations. Users can assign tasks and trigger actions just by conversing with our agentic AI, Zia, streamlining their workflows and empowering data-driven decisions. Seamlessly embed Ask Zia into your custom or business applications to deliver contextual insights and actions. Enrich your analysis with automated insights by using our NLG-powered narration engine, Zia Insights. With diagnostic analytics for smarter decision-making, Zia Insights takes automated insights to the next level by bubbling up key drivers for particular business tasks. Enumerate complex business scenarios with what-if analyses, forecast KPIs, uncover trends and patterns with advanced analytical capabilities. Leverage cognitive analysis for keyword extraction and sentiment analysis, and more. Evaluate the best ML models with no-code assistance or develop custom models and functions using Python Code Studio. Zoho Analytics comes with pre-packed ML models (AutoML) that allow you to evaluate and pick the best model for your use case. Alternatively custom models and functions using Python Code Studio Embed our full-fledged analytics platform into other software applications. Craft and present immersive data stories through slideshows or purpose-built analytics portals. Collaborate securely through contextual comment threads and real-time messaging. Zoho Analytics has a robust set of APIs that enables elaborate customization and highly extensible low-code and no-code integration with any technology stack. It also offers a high degree of deployment flexibility (private, public, multi-cloud, and on-premises) and platform extensibility (professional services, partner support, and marketplace). Zoho Analytics is modern and scalable, and it can readily match growing data volumes and usage. Its time-tested and accredited enterprise-grade security features and governance framework ensure continuous data management and stewardship. On top of everything else, the TCO for Zoho Analytics—including licensing, implementation, customization, training, and support—is the lowest in our market. [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=620&secure%5Bdisplayable_resource_id%5D=620&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=620&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=3431&secure%5Bresource_id%5D=620&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fanalytics-platforms&secure%5Btoken%5D=a4cfda32bbe5236668878cd91b9e0c035b6d97bce1d1a16324bf9d2adaaa87f8&secure%5Burl%5D=https%3A%2F%2Fwww.zoho.com%2Fanalytics%2F%3Futm_source%3DG2%26utm_medium%3Dcpc%26utm_campaign%3DAnalytics_Platforms&secure%5Burl_type%5D=custom_url) --- ## Buyer Guide: Key Questions for Choosing Analytics Platforms Software ### What do Analytics Platforms do? When I explain analytics platforms, I frame them as systems that help teams turn business data into usable insight. These platforms bring dashboards, reports, data modeling, metric exploration, visualizations, and insight sharing into one workflow. Instead of relying on scattered spreadsheets, static reports, or disconnected data views, teams can access information faster, understand performance more clearly, and make decisions with more confidence. ### Why do businesses use Analytics Platforms? From the G2 reviewer patterns I evaluated, businesses use Analytics Platforms because data sits across many systems and takes too much manual effort to organize. Users mention fragmented reports, delayed insight, inconsistent metrics, and hard-to-present data. Common benefits include: - Faster dashboard and report creation. - Clearer visibility into KPIs, sales, marketing, operations, and product data. - Stronger exploration through filters, drilldowns, SQL, and visual workflows. - Easier sharing of insights with teams and stakeholders. - Better integration with databases, cloud platforms, spreadsheets, CRM tools, and warehouses. ### Who uses Analytics Platforms primarily? After I evaluated G2 reviewer roles, I found that Analytics Platforms serve technical and business users. - **Data analysts** build dashboards, reports, and recurring performance views. - **BI teams** manage metrics, models, and governed workflows. - **Data engineers** connect sources and prepare datasets. - **Data scientists** use notebooks, models, and advanced analytics features. - **Business analysts** translate data into operational decisions. - **Executives** use dashboards to understand trends. ### What types of Analytics Platforms should I consider? From the way reviewers describe the category, buyers should compare several product types: - **BI and dashboard platforms** for reports, visualization, and executive views. - **Self-service analytics tools** for fast business exploration. - **Cloud analytics platforms** for larger datasets and scalable processing. - **Data science and notebook platforms** for SQL, Python, models, and collaboration. - **Embedded analytics tools** for customer-facing dashboards. - **Semantic layer platforms** for shared metrics and reusable definitions. ### What are the core features to look for in Analytics Platforms? When I break down G2 reviews for this category, I look closely at the themes users repeatedly mention: - Dashboard and report builders with flexible layouts that help teams organize business data into views people can actually use. - Data visualization, charting, and interactive filters that help users explore trends, compare performance, and understand metrics faster. - Connectors for databases, spreadsheets, cloud tools, and business applications that help bring data from different systems into one place. - SQL support, data modeling, and calculated metrics that help analysts define, structure, and customize business logic. - AI-assisted search or automated insights that help users find patterns and answers without building every report manually. - Collaboration, permissions, scheduled delivery, and sharing controls that help teams distribute insights securely and consistently. - Performance controls for complex dashboards that help reports load reliably even when data volume or usage grows. - Documentation, training resources, and responsive support that help teams onboard faster and troubleshoot issues with less friction. ### What trends are shaping Analytics Platforms right now? From the G2 review patterns I evaluated, several trends stand out: - **AI-assisted analytics** is helping users ask questions, generate summaries, and discover insights faster. - **Self-service reporting** is becoming more important as business teams look for answers without depending on analysts for every request. - **Cloud and application integrations** are expanding as companies connect analytics platforms to more data sources and business systems. - **Governed metrics and semantic layers** are gaining value as teams work to keep definitions consistent across dashboards and reports. - **Performance optimization** remains a priority as users expect complex dashboards to load quickly and reliably. - **Usability and guided setup** are shaping adoption as buyers look for platforms that are powerful without creating a steep learning curve. ### How should I choose Analytics Platforms? For me, the strongest Analytics Platforms fit depends on data sources, governance needs, and scale. I would prioritize products reviewers praise for intuitive dashboards, flexible visualization, strong integrations, reliable performance, and clear collaboration. I would also examine concerns around customization, complex setup, pricing, learning curve, and AI accuracy before making a final choice. --- ## What Are the Top-Rated Analytics Platforms Products in 2026? ### 1. [Tableau](https://www.g2.com/products/tableau/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 3,549 **Why buyers love it?:** A recurring pattern in Tableau’s G2 feedback when I reviewed it was that its strength in visual exploration across varied data sources. Reviewers highlight simple dashboard creation, flexible integrations, clear KPI views, and fast access to business insights for sales, operations, and leadership use cases. The product reads as a fit for teams that want polished visual dashboards and interactive data exploration across multiple systems. Users also note friction with dashboard layout control, data prep, live connection speed, pricing, and some API gaps. ### What Do G2 Reviewers Say About Tableau? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate Tableau for its **ease of use** , allowing seamless creation of interactive dashboards and reports. - Users value Tableau for its **simplicity in data visualization** , enabling clear insights from complex data effortlessly. - Users value the **intuitive and powerful data visualization** of Tableau, enabling clear insights and effective decision-making. - Users love the **ease of use and powerful reporting features** in Tableau, enabling effective data visualization effortlessly. - Users enjoy the **intuitive design** of Tableau, facilitating easy creation of impactful data visualizations and dashboards. **Cons:** - Users find the **learning curve steep** , leading to challenges during onboarding and integration with other tools. - Users report **learning difficulties** with Tableau's advanced features and collaboration tools, finding it more complex than expected. - Users find Tableau's pricing to be **expensive** and believe it hinders accessibility for larger organizations. - Users experience **slow performance** when handling large datasets, leading to frustrating delays and inefficiencies. - Users find the **onboarding process complex** , requiring extra steps and making it harder to transition from MS products. #### Key Features - Steps to Answer - Calculated Fields - Predictive Analytics - Data Modeling - Data Mining #### What Are Recent G2 Reviews of Tableau? **"[Powerful, Flexible Visualizations with Minor Performance Delays](https://www.g2.com/survey_responses/tableau-review-11907092)"** **Rating:** 5.0/5.0 stars *— Raghini G.* [Read full review](https://www.g2.com/survey_responses/tableau-review-11907092) --- **"[Instant Insights with Interactive Dashboards](https://www.g2.com/survey_responses/tableau-review-12784839)"** **Rating:** 5.0/5.0 stars *— Rahul S.* [Read full review](https://www.g2.com/survey_responses/tableau-review-12784839) --- #### 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 ### 2. [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **Average Rating:** 4.5/5.0 **Total Reviews:** 1,576 **Why buyers love it?:** When I reviewed Microsoft Power BI’s G2 feedback, the strongest theme was its role in turning complex datasets into interactive dashboards inside a familiar Microsoft environment. Reviewers highlight Excel, Azure, SQL Server, and broader Microsoft integrations, along with visuals that make analysis easier to share. The product reads as a strong fit for teams that need dashboard creation, data modeling, and business reporting connected to existing Microsoft workflows. Users also cite a learning curve for advanced DAX, performance strain with very large datasets, customization limits, licensing complexity, and occasional refresh issues. ### What Do G2 Reviewers Say About Microsoft Power BI? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** in Microsoft Power BI, making data analysis and reporting straightforward and efficient. - Users value the **data visualization capabilities** of Microsoft Power BI, enhancing insights from large data sets effectively. - Users appreciate the **seamless software integrations** of Power BI, enhancing data analysis and visualization capabilities effortlessly. - Users value the **powerful analytics capabilities** of Microsoft Power BI, enhancing data insights and decision-making efficiency. - Users appreciate the **powerful charting features** of Microsoft Power BI, enabling clear visualizations and easy report creation. **Cons:** - Users find the **learning curve steep** , especially for beginners, making it tough to effectively use Power BI. - Users experience **slow performance** with Microsoft Power BI when managing large datasets, impacting efficiency and usability. - Users experience **performance issues** with large datasets, causing slowdowns and complicating the overall experience with Power BI. - Users struggle with the **complex data modeling** in Power BI, facing a steep learning curve and performance issues. - Users face **limited customization** options in Power BI, finding the selection of free visuals insufficient for their needs. #### Key Features - Reports Interface - Data Column Filtering - Predictive Analytics - Data Modeling - Connectors #### What Are Recent G2 Reviews of Microsoft Power BI? **"[No-Code Microsoft Analytics with Easy Data Connections and Drag-and-Drop Dashboards](https://www.g2.com/survey_responses/microsoft-power-bi-review-12894515)"** **Rating:** 4.5/5.0 stars *— Ashutha K.* [Read full review](https://www.g2.com/survey_responses/microsoft-power-bi-review-12894515) --- **"[Zero-Code Dashboards with Easy Data Transformations and One-Click Publishing](https://www.g2.com/survey_responses/microsoft-power-bi-review-12864007)"** **Rating:** 4.5/5.0 stars *— Swati J.* [Read full review](https://www.g2.com/survey_responses/microsoft-power-bi-review-12864007) --- #### What Are G2 Users Discussing About Microsoft Power BI? - [What is Microsoft Power BI Desktop used for?](https://www.g2.com/discussions/what-is-microsoft-power-bi-desktop-used-for) - 4 comments, 1 upvote - [What are some of the top features of Microsoft BI?](https://www.g2.com/discussions/what-are-some-of-the-top-features-of-microsoft-bi) - 3 comments - [Is Power BI a Microsoft tool?](https://www.g2.com/discussions/is-power-bi-a-microsoft-tool) - 5 comments, 3 upvotes ### 3. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) **Average Rating:** 4.3/5.0 **Total Reviews:** 755 **Why buyers love it?:** The signal I found in SAS Viya’s G2 feedback was its appeal for advanced analytics work that spans coding, model development, and cloud-scale data processing. Reviewers highlight strong performance, memory handling, multi-language support, and a modern environment that extends familiar SAS workflows. The product reads as a fit for organizations that need statistical analysis, machine learning, and governed analytics in a cloud-based platform. Users also mention setup complexity, a steep learning curve for new users, migration friction from older SAS environments, and high licensing or implementation costs. ### What Do G2 Reviewers Say About SAS Viya? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **user-friendly interface** of SAS Viya, making complex analytics accessible to all skill levels. - Users appreciate the **advanced analytical capabilities** of SAS Viya, making data processing and decision-making seamless and efficient. - Users benefit from the **sophisticated analytical capabilities** of SAS Viya, enhancing real-time decision-making and insights. - Users appreciate the **end-to-end data lifecycle tooling** of SAS Viya, enhancing insights and strategic decision-making capabilities. - Users appreciate the **user-friendly interface** of SAS Viya, making complex analysis accessible to all skill levels. **Cons:** - Users find it **difficult to navigate and use** SAS Viya, especially newcomers and non-technical individuals. - Users find the **visualization complexity** in SAS Viya challenging, especially for non-technical users and newcomers. - Users find the **learning curve steep** , making it challenging for non-technical users to navigate reports and dashboards. - Users find the **difficult learning curve** discouraging, especially when needing to navigate reports and dashboards effectively. - Users find the **pricing expensive** and often vague, making it challenging to assess value upfront. #### Key Features - Steps to Answer - Calculated Fields - Data Visualization - WYSIWYG Report Design - Data Visualizations #### What Are Recent G2 Reviews of SAS Viya? **"[Powerful & Transforming Data into Decisions—Effortlessly and Intelligently.](https://www.g2.com/survey_responses/sas-viya-review-12682824)"** **Rating:** 4.5/5.0 stars *— Venkatesh D.* [Read full review](https://www.g2.com/survey_responses/sas-viya-review-12682824) --- **"[SAS Viya is a Powerful Analytics](https://www.g2.com/survey_responses/sas-viya-review-11702846)"** **Rating:** 5.0/5.0 stars *— Deependra G.* [Read full review](https://www.g2.com/survey_responses/sas-viya-review-11702846) --- #### 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 ### 4. [Amazon QuickSight](https://www.g2.com/products/amazon-quicksight/reviews) **Average Rating:** 4.3/5.0 **Total Reviews:** 673 **Why buyers love it?:** Amazon QuickSight’s G2 feedback pointed to a product valued most when analytics sits close to AWS data and infrastructure. Reviewers highlight serverless setup, AWS integration, SPICE performance, calculated metrics, interactive dashboards, live data updates, and newer AI-assisted exploration features. From my evaluation, the product reads as a fit for teams that want BI dashboards inside an AWS-centered environment without heavy infrastructure management. Users also mention limited visual customization, fewer chart options, a less intuitive interface, slower downloads, and a learning curve for non-technical users. ### What Do G2 Reviewers Say About Amazon QuickSight? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **seamless integration** with AWS services, enhancing their ability to create interactive dashboards effortlessly. - Users find Amazon QuickSight to be **very user-friendly** , seamlessly integrating with AWS and offering responsive dashboards. - Users appreciate the **easy integrations** of Amazon QuickSight with AWS, enhancing convenience and reducing development overhead. - Users highlight the **interactive dashboards** of Amazon QuickSight, enabling effective data visualization for real-time insights. - Users find Amazon QuickSight's **dashboard management** to be intuitive, enhancing collaboration and data insights effortlessly. **Cons:** - Users find **limited customization options** in Amazon QuickSight hinder their ability to tailor dashboards effectively. - Users find the **learning curve challenging** , requiring prior AWS knowledge for effective use of QuickSight. - Users note the **limited visualization options** in QuickSight, making it difficult to achieve desired dashboard designs. - Users express concern over **missing features** in QuickSight, especially when compared to competitors like Power BI and Tableau. - Users find the **poor interface design** of Amazon QuickSight limits intuitive use and deeper customization options. #### Key Features - Reports Interface - Calculated Fields - Data Visualization - Data Transformation - Scripting #### What Are Recent G2 Reviews of Amazon QuickSight? **"[Turns Raw Data into Interactive Dashboards for Better Trend Monitoring](https://www.g2.com/survey_responses/amazon-quicksight-review-12740199)"** **Rating:** 4.0/5.0 stars *— Aviral G.* [Read full review](https://www.g2.com/survey_responses/amazon-quicksight-review-12740199) --- **"[Amazon QuickSight’s New QuickSuite UI and Chat/AI Search Make Reporting Easier](https://www.g2.com/survey_responses/amazon-quicksight-review-12532508)"** **Rating:** 5.0/5.0 stars *— SAURABH B.* [Read full review](https://www.g2.com/survey_responses/amazon-quicksight-review-12532508) --- #### 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 ### 5. [GoodData.AI](https://www.g2.com/products/gooddata-ai/reviews) **Average Rating:** 4.2/5.0 **Total Reviews:** 574 **Product Description:** 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. ### What Do G2 Reviewers Say About GoodData.AI? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of GoodData.AI, citing its intuitive interface and efficient automation features. - Users appreciate the **clean and customizable dashboards** of GoodData.AI, simplifying complex data presentation for all users. - Users value the **quick and effective integrations** of GoodData.AI, enhancing their overall user experience and functionality. - Users find GoodData.AI's **intuitive user interface** easy to navigate, streamlining the data reporting and dashboard creation process. - Users appreciate the **customization options** of GoodData.AI, allowing tailored solutions for diverse business insights and needs. **Cons:** - Users find the **learning curve steep** for GoodData.AI, especially those without a background in relational databases. - Users express concern about **missing features** in GoodData.AI, particularly in documentation and graphical reporting capabilities. - Users find the **learning difficulty** with GoodData.AI challenging due to the complex data models and MAQL language. - Users find GoodData.AI to be **complex to use** , especially with advanced features and data modeling challenges. - Users find the **limited customization** options of GoodData.AI restrictive, hindering their ability to tailor the data model effectively. #### What Are Recent G2 Reviews of GoodData.AI? **"[Effortless Drag-and-Drop Dashboards with Smart AI Visualization Suggestions](https://www.g2.com/survey_responses/gooddata-ai-review-12849514)"** **Rating:** 5.0/5.0 stars *— Ivan B.* [Read full review](https://www.g2.com/survey_responses/gooddata-ai-review-12849514) --- **"[Flexible and powerful platform for embedded analytics](https://www.g2.com/survey_responses/gooddata-ai-review-11210819)"** **Rating:** 4.0/5.0 stars *— Gina H.* [Read full review](https://www.g2.com/survey_responses/gooddata-ai-review-11210819) --- ### 6. [Yellowfin BI](https://www.g2.com/products/yellowfin-bi/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 418 **Why buyers love it?:** Yellowfin BI’s G2 feedback centered on making analytics more approachable through guided dashboard and report experiences. Reviewers highlight intuitive navigation, drag-and-drop report creation, visual exploration, automated insights, data storytelling, and browser or mobile access. To me the product reads as a fit for teams that want BI outputs that explain results rather than only display charts. Users also cite slower performance with complex datasets, advanced-feature learning effort, and a need for stronger tutorials and enablement resources. ### What Do G2 Reviewers Say About Yellowfin BI? *AI-generated summary from verified user reviews* **Pros:** - Users value the **user-friendly interface** of Yellowfin BI, allowing effortless dashboard and report creation for all expertise levels. - Users value the **user-friendly data visualization** capabilities of Yellowfin BI, enabling effortless report creation and insight sharing. - Users value Yellowfin BI for its **intuitive setup** , enabling quick, hassle-free data exploration and compelling storytelling. - Users highlight the **user-friendly interface** of Yellowfin BI, enabling easy dashboard creation and effective collaboration. - Users appreciate the **easy dashboard customization** of Yellowfin BI, enabling quick setup and effective data storytelling. **Cons:** - Users often find a **steep learning curve** with Yellowfin BI, requiring time to master advanced features and customization. - Users experience **performance slowdown** when handling large datasets in Yellowfin BI, impacting overall report efficiency. - Users find the **slow performance** of Yellowfin BI concerning, especially with large or complex datasets affecting efficiency. - Users experience **performance issues** with slow dashboard loading and lengthy updates, particularly with large datasets and complex setups. - Users find **limited customization** in Yellowfin BI hinders advanced analytics and makes deep analysis more challenging. #### Key Features - Reports Interface - Collaboration / Workflow - Data Visualization - Data Transformation - Connectors #### What Are Recent G2 Reviews of Yellowfin BI? **"[Yellowfin BI Excels at Data Storytelling, Collaboration, and AI-Assisted Insights](https://www.g2.com/survey_responses/yellowfin-bi-review-12809222)"** **Rating:** 4.5/5.0 stars *— Rinalon E.* [Read full review](https://www.g2.com/survey_responses/yellowfin-bi-review-12809222) --- **"[Brilliant Data Storytelling and Robust Dashboards with Yellowfin BI](https://www.g2.com/survey_responses/yellowfin-bi-review-12827644)"** **Rating:** 4.5/5.0 stars *— Luciana S.* [Read full review](https://www.g2.com/survey_responses/yellowfin-bi-review-12827644) --- #### What Are G2 Users Discussing About Yellowfin BI? - [What is Yellowfin BI used for?](https://www.g2.com/discussions/what-is-yellowfin-bi-used-for) - [What should I look for in a BI tool?](https://www.g2.com/discussions/what-should-i-look-for-in-a-bi-tool) - [What is the best BI software?](https://www.g2.com/discussions/what-is-the-best-bi-software) - 1 comment ### 7. [Deepnote](https://www.g2.com/products/deepnote/reviews) **Average Rating:** 4.5/5.0 **Total Reviews:** 377 **Product Description:** Deepnote is a data workspace where agents and humans work together. It's designed to simplify data exploration, accelerate analysis, and quickly deliver actionable insights for you and your team. Unlike outdated tools such as Jupyter, Deepnote is built with the next decade in mind. Deepnote gives anyone working with data superpowers. It unifies your data workflow through an integrated semantic layer, preparing your data for advanced AI applications. You can also leverage our AI data copilot to chat with your data, create charts, write code, or turn your AI notebooks into fully-fledged data dashboards or apps. Combine data, SQL or Python code, and visualizations side-by-side on a flexible canvas - enhanced with cutting-edge AI reasoning models. 🤖 Analyze with AI • Generate code and visualizations by describing your goal. • Auto-write, run, and debug code with AI. • Move faster with context-aware AI suggestions. 🔗 Unify • Connect to 60+ data sources like BigQuery, Snowflake, and PostgreSQL. • Combine Python and SQL in one notebook. • Build reusable ETL, analytics, and metric modules. • Create a semantic layer with shared definitions and trusted metrics. ⚖️ Scale • Instantly boost compute power, more included than Colab. • Schedule jobs and get notified with fresh results. • Organize work in projects and folders for team clarity. • Manage workflows via REST API. 🚀 Launch • Turn notebooks into dashboards or data apps, natively or with Streamlit. • Let users explore data with interactive inputs. • Share secure, live apps in one click. ### What Do G2 Reviewers Say About Deepnote? *AI-generated summary from verified user reviews* **Pros:** - Users find Deepnote's **ease of use** invaluable, facilitating smooth collaboration and efficient data analysis. - Users highlight the **seamless collaboration** features of Deepnote, enhancing teamwork and project efficiency through real-time editing. - Users value the **real-time collaboration** features of Deepnote, enhancing team connectivity and data analysis efficiency. - Users value the **easy integrations** in Deepnote, facilitating seamless access to various data environments and services. - Users appreciate the **ease of data management** in Deepnote, simplifying analytics and enhancing team collaboration effectively. **Cons:** - Users experience **slow performance** especially with large datasets, affecting the application's agility and usability. - Users find the **limited features** of Deepnote restricts their ability to effectively build and integrate AI applications. - Users experience **data management issues** in Deepnote, including slowness, kernel crashes, and unintuitive file handling. - Users have experienced **lagging performance** with Deepnote, especially when handling larger datasets or multiple requests. - Users experience **slow loading times** with Deepnote, which can hinder productivity and complicate working on larger projects. #### What Are Recent G2 Reviews of Deepnote? **"[Deepnote’s Real-Time Collaboration and Cloud Notebooks Shine](https://www.g2.com/survey_responses/deepnote-review-12687317)"** **Rating:** 5.0/5.0 stars *— Jolina Mae A.* [Read full review](https://www.g2.com/survey_responses/deepnote-review-12687317) --- **"[Clarity for complex nutrition work](https://www.g2.com/survey_responses/deepnote-review-12699174)"** **Rating:** 5.0/5.0 stars *— Marine A.* [Read full review](https://www.g2.com/survey_responses/deepnote-review-12699174) --- #### What Are G2 Users Discussing About Deepnote? - [How do you use a deep note?](https://www.g2.com/discussions/how-do-you-use-a-deep-note) - [Is Deepnote open source?](https://www.g2.com/discussions/is-deepnote-open-source) - [Is Deepnote good?](https://www.g2.com/discussions/is-deepnote-good) - 1 comment ### 8. [Looker](https://www.g2.com/products/looker/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 1,580 **Why buyers love it?:** In Looker’s G2 feedback, the most consistent thread was governed data access paired with shareable dashboards. Reviewers highlight quick report creation, GA and business dashboard use cases, flexible customization, team sharing, and integrations that help stakeholders review common metrics. The product reads to me as a fit for organizations that need reusable BI views and consistent reporting across teams. Users also cite slow performance in large dashboards, limits around custom metrics or plots, manual blending, dated chart experiences, and a learning curve. ### What Do G2 Reviewers Say About Looker? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **ease of use** of Looker, appreciating its intuitive drag-and-drop interface for all skill levels. - Users appreciate the **dynamic and flexible reporting** capabilities of Looker, enhancing insights and decision-making across platforms. - Users find Looker’s **easy integrations** with various data sources to be a significant advantage for analytics. - Users value the **seamless integrations** with tools like Salesforce, enhancing data analysis and insights quality. - Users appreciate the **dynamic and real-time reporting** capabilities of Looker, enhancing their analysis and decision-making processes. **Cons:** - Users find the **learning curve steep** with Looker, particularly for those unfamiliar with LookML and advanced features. - Users find Looker to have a **steep learning curve** , making it challenging for beginners to utilize effectively. - Users experience **slow loading** times with Looker, especially when handling large datasets, impacting overall efficiency. - Users often face **slow performance** with Looker, especially during complex data operations, affecting timely deliverables. - Users find Looker’s **complexity** challenging due to limited visuals and a steep learning curve, especially with LookML. #### Key Features - Steps to Answer - Search - Predictive Analytics - Integration APIs - Retroactive Reporting #### What Are Recent G2 Reviews of Looker? **"[Transforms Data, But Challenging for Beginners](https://www.g2.com/survey_responses/looker-review-12784757)"** **Rating:** 5.0/5.0 stars *— Rahul S.* [Read full review](https://www.g2.com/survey_responses/looker-review-12784757) --- **"[Powerful once it's set up properly, that's once is doing a lot of work in that sentence](https://www.g2.com/survey_responses/looker-review-12863840)"** **Rating:** 4.5/5.0 stars *— Verified User in Information Technology and Services* [Read full review](https://www.g2.com/survey_responses/looker-review-12863840) --- #### What Are G2 Users Discussing About Looker? - [What is Looker used for?](https://www.g2.com/discussions/what-is-looker-used-for) - 1 comment - [Why is looker so powerful?](https://www.g2.com/discussions/why-is-looker-so-powerful) - [Is looker an ETL tool?](https://www.g2.com/discussions/is-looker-an-etl-tool) - 3 comments ### 9. [Splunk Enterprise](https://www.g2.com/products/splunk-enterprise/reviews) **Average Rating:** 4.3/5.0 **Total Reviews:** 414 **Product Description:** Find out what is happening in your business and take meaningful action quickly with Splunk Enterprise. Automate the collection, indexing and alerting of machine data that's critical to your operations. Uncover the actionable insights from all your data — no matter the source or format. Leverage artificial intelligence and machine learning for predictive and proactive business decisions. ### What Do G2 Reviewers Say About Splunk Enterprise? *AI-generated summary from verified user reviews* **Pros:** - Users enjoy the **ease of use** of Splunk Enterprise, simplifying data analysis and visualization for better insights. - Users highlight the **robust data ingestion** capabilities of Splunk Enterprise, effectively managing large volumes from various sources. - Users value the **seamless integrations** of Splunk Enterprise, enhancing data management across diverse systems effortlessly. - Users admire the **robust data analysis and visualization features** of Splunk Enterprise for efficient troubleshooting and insights. - Users appreciate the **brilliant visualization capabilities** of Splunk Enterprise, aiding in effective data analysis and presentation. **Cons:** - Users find Splunk Enterprise **too expensive** , particularly for large organizations with extensive workloads and high renewal costs. - Users find the **learning curve steep** for Splunk Enterprise, making it challenging for newcomers to effectively utilize its features. - Users experience **slow performance** in Splunk Enterprise, often facing delays and challenges with troubleshooting issues. - Users find the **complex configuration** of Splunk Enterprise a challenge, impacting performance optimization and user-friendliness. - Users find the **pricing issues** of Splunk Enterprise burdensome, especially with costs and storage limitations affecting performance. #### What Are Recent G2 Reviews of Splunk Enterprise? **"[Splunk Enterprise Makes Endpoint Data Collection and Troubleshooting Easy at Scale](https://www.g2.com/survey_responses/splunk-enterprise-review-6749798)"** **Rating:** 4.0/5.0 stars *— Robert B.* [Read full review](https://www.g2.com/survey_responses/splunk-enterprise-review-6749798) --- **"[SPL search and dashboards are really useful](https://www.g2.com/survey_responses/splunk-enterprise-review-12547655)"** **Rating:** 4.0/5.0 stars *— Nishith J.* [Read full review](https://www.g2.com/survey_responses/splunk-enterprise-review-12547655) --- #### What Are G2 Users Discussing About Splunk Enterprise? - [What is Splunk Enterprise used for?](https://www.g2.com/discussions/what-is-splunk-enterprise-used-for) - 1 comment - [What is the difference between Splunk Enterprise and Splunk Enterprise Security?](https://www.g2.com/discussions/splunk-enterprise-what-is-the-difference-between-splunk-enterprise-and-splunk-enterprise-security) - 1 comment - [What are Splunk Enterprise components?](https://www.g2.com/discussions/what-are-splunk-enterprise-components) - 1 comment ### 10. [IBM Cognos Analytics](https://www.g2.com/products/ibm-cognos-analytics/reviews) **Average Rating:** 4.1/5.0 **Total Reviews:** 394 **Why buyers love it?:** IBM Cognos Analytics’ G2 feedback focused on report creation, dashboard delivery, and access to historical business data. Reviewers highlight clear visual outputs, customizable reports, long-range order or transaction history, Excel export, and support for executive-facing presentations. The product reads as a fit for enterprises that need structured BI reporting with flexible views of established business data. Users also cite an outdated interface, slow report generation, a learning curve for new users, and complexity in advanced report creation. ### What Do G2 Reviewers Say About IBM Cognos Analytics? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** in IBM Cognos Analytics, enabling quick and intuitive data visualization and analysis. - Users appreciate the **in-depth adaptable dashboards and reports** of IBM Cognos Analytics, enabling thorough data analysis and insights. - Users enjoy the **intuitive user interface** of IBM Cognos Analytics, making data visualization effortless and engaging. - Users appreciate the **dashboard customization** in IBM Cognos Analytics, transforming complex data into clear visuals effortlessly. - Users appreciate the **efficiency** of IBM Cognos Analytics, benefiting from quick report generation and clear visualizations. **Cons:** - Users find the **learning curve steep** , requiring significant time and training to effectively utilize IBM Cognos Analytics. - Users find the pricing of IBM Cognos Analytics to be **expensive** , impacting overall satisfaction despite its features. - Users find the **complexity** of IBM Cognos Analytics challenging, making report building difficult without extensive training. - Users find the **complex usage** of IBM Cognos Analytics challenging, leading to a steep learning curve and cumbersome reporting. - Users find **learning difficult** , especially in locating historical reports and building reports without extensive training. #### Key Features - Reports Interface - Data Column Filtering - Predictive Analytics - Data Transformation - Connectors #### What Are Recent G2 Reviews of IBM Cognos Analytics? **"[Powerful Data Analysis with Intuitive Drag-and-Drop Visualizations](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-12153976)"** **Rating:** 4.5/5.0 stars *— Konjengbam M.* [Read full review](https://www.g2.com/survey_responses/ibm-cognos-analytics-review-12153976) --- **"[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) --- #### 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 ### 11. [Hex](https://www.g2.com/products/hex-tech-hex/reviews) **Average Rating:** 4.5/5.0 **Total Reviews:** 392 **Why buyers love it?:** The pattern that I found in Hex’s G2 feedback was its usefulness for analysts who move between code, notebooks, and shareable data apps. Reviewers highlight an intuitive interface, SQL and Python in one workspace, AI-assisted query and chart generation, custom controls, and flexible exploration. The product reads as a fit for teams that want collaborative analysis to move from notebook work into stakeholder-facing outputs. Users also cite heavy-query slowness, app-builder layout constraints, connection stability issues, CSV handling problems, and challenges preserving ad hoc results. ### What Do G2 Reviewers Say About Hex? *AI-generated summary from verified user reviews* **Pros:** - Users highlight the **user-friendliness** of Hex, making data integration and analysis incredibly straightforward and efficient. - Users appreciate the **ease of combining SQL with Python** , enhancing their data analysis experience and accessibility. - Users value the **seamless data integration** in Hex, enhancing their BI reporting and exploratory data analysis experiences. - Users appreciate the **seamless SQL querying** capabilities of Hex, especially with its AI assistance and notebook functionality. - Users love the **seamless integration of SQL and Python** in Hex, significantly speeding up data analysis and visualization. **Cons:** - Users express frustration over **limited features** , wishing for more graph types and better styling options in Hex. - Users note the **missing features** in Hex regarding data privacy and limited controls for effective analytics management. - Users find Hex **lacking features** such as advanced controls, efficient filters, and performance for large data sets. - Users find Hex's **limited visualization capabilities** frustrating due to data size restrictions and inadequate filtering options. - Users find **data management issues** in Hex, especially with organization and complexity in notebooks and components. #### Key Features - Steps to Answer - Collaboration / Workflow - Predictive Analytics - WYSIWYG Report Design - Drag and Drop #### What Are Recent G2 Reviews of Hex? **"[Effortless Data Analysis with Powerful AI](https://www.g2.com/survey_responses/hex-review-12262172)"** **Rating:** 5.0/5.0 stars *— Hunter P.* [Read full review](https://www.g2.com/survey_responses/hex-review-12262172) --- **"[Amazing AI and SQL Autocomplete That Speeds Up My Work](https://www.g2.com/survey_responses/hex-review-12687305)"** **Rating:** 4.0/5.0 stars *— Paco R.* [Read full review](https://www.g2.com/survey_responses/hex-review-12687305) --- #### What Are G2 Users Discussing About Hex? - [What is Hex Technologies used for?](https://www.g2.com/discussions/what-is-hex-technologies-used-for) ### 12. [Alteryx](https://www.g2.com/products/alteryx/reviews) **Average Rating:** 4.6/5.0 **Total Reviews:** 774 **Why buyers love it?:** When I reviewed Alteryx’s G2 feedback, the strongest theme was reducing manual data preparation through visual workflows. Reviewers highlight drag-and-drop data manipulation, fast blending across sources, large dataset handling, Excel-heavy workflow acceleration, automation, and improved report efficiency. The product reads as a fit for teams that need repeatable preparation and analysis workflows without line-by-line code. Users also mention slower performance in complex workflows, unclear error guidance, high memory use, and concerns around cloud processing requirements. ### What Do G2 Reviewers Say About Alteryx? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** in Alteryx, making data analytics accessible for everyone through simple drag and drop. - Users appreciate the **automation capabilities** of Alteryx, simplifying data processes and enhancing analytical efficiency. - Users find Alteryx **very intuitive** , making it easy for non-technical individuals to learn and use effectively. - Users find that Alteryx makes **learning technology easy** , thanks to its intuitive design and supportive community. - Users value the **efficiency** of Alteryx in managing data quickly and effortlessly, streamlining analysis processes effectively. **Cons:** - Users find Alteryx's **expensive pricing** challenging for small teams and startups, making widespread access difficult. - Users note a **learning curve** for mastering complex features, requiring time and effort to fully leverage Alteryx. - Users find the lack of **integrated reporting features** in Alteryx requires additional tools for a complete solution. - Users find the **learning difficulty** of Alteryx steep, making it challenging for new users to adapt quickly. - Users find that **slow performance** hinders the analysis of large workflows, causing frustration during data processing. #### Key Features - Data Column Filtering - Data Visualization - WYSIWYG Report Design - Data Unification - Data Visualization #### What Are Recent G2 Reviews of Alteryx? **"[Easy, Time-Saving Data Automation with Alteryx’s Drag-and-Drop Workflows](https://www.g2.com/survey_responses/alteryx-review-12594796)"** **Rating:** 4.0/5.0 stars *— Kapil S.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-12594796) --- **"[powerful data prep made simple with drag-and-drop](https://www.g2.com/survey_responses/alteryx-review-12714902)"** **Rating:** 4.0/5.0 stars *— Sravya A.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-12714902) --- ### 13. [ThoughtSpot](https://www.g2.com/products/thoughtspot/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 317 **Product Description:** ThoughtSpot is the Agentic Analytics Platform company for the enterprise. With natural language and AI, ThoughtSpot empowers everyone in an organization to ask data questions, get answers, and take action. Code-first for data teams and code-free for business users, ThoughtSpot is intuitive enough for anyone to use, yet built to handle large, complex cloud data at scale. Customers like Coca-Cola, Hilton Worldwide, and Capital One are unlocking the full potential of their data with ThoughtSpot. ### What Do G2 Reviewers Say About ThoughtSpot? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of ThoughtSpot, enjoying fast and intuitive access to vital data. - Users appreciate the **user-friendly interface** of ThoughtSpot, enabling effortless data handling and reporting without technical assistance. - Users value the **intuitive analytics** of ThoughtSpot, empowering everyone to easily explore and visualize data insights. - Users appreciate ThoughtSpot's **intuitive interface** , making data analytics accessible and easy for everyone to use. - Users highlight the **effective data visualization** in ThoughtSpot, making analysis straightforward and supporting informed decision-making. **Cons:** - Users experience a **steep learning curve** with ThoughtSpot, finding the tool non-intuitive and challenging to use initially. - Users note the **missing features** in ThoughtSpot, with some key data still in development and limited UI customization. - Users face **complexity issues** with ThoughtSpot, finding it non-intuitive and challenging for building formulas and metrics. - Users face significant **learning difficulties** with ThoughtSpot, finding it unintuitive and lacking proper guidance for effective use. - Users note that **customization options are limited** , impacting flexibility and user experience in ThoughtSpot. #### What Are Recent G2 Reviews of ThoughtSpot? **"[Intuitive Natural Language Analytics That Speeds Insights and Integrates Smoothly with Snowflake](https://www.g2.com/survey_responses/thoughtspot-review-12714758)"** **Rating:** 4.5/5.0 stars *— Verified User in Health, Wellness and Fitness* [Read full review](https://www.g2.com/survey_responses/thoughtspot-review-12714758) --- **"[Revolutionized Insights with Conversational AI](https://www.g2.com/survey_responses/thoughtspot-review-12592167)"** **Rating:** 5.0/5.0 stars *— Farid V.* [Read full review](https://www.g2.com/survey_responses/thoughtspot-review-12592167) --- #### What Are G2 Users Discussing About ThoughtSpot? - [What is ThoughtSpot used for?](https://www.g2.com/discussions/thoughtspot-what-is-thoughtspot-used-for) - [What does ThoughtSpot do?](https://www.g2.com/discussions/what-does-thoughtspot-do) - 1 comment - [Is ThoughtSpot a public company?](https://www.g2.com/discussions/is-thoughtspot-a-public-company) ### 14. [Sigma](https://www.g2.com/products/sigma-computing-sigma/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 543 **Why buyers love it?:** The clearest pattern I saw in Sigma’s G2 feedback was its appeal to teams that want cloud-warehouse data in a familiar analytical interface. Reviewers highlight easy access to critical data, dashboard interactivity, large dataset handling, Snowflake connectivity, and the ability to explore data directly inside workbooks. The product reads as a fit for business and data teams that need self-service analytics without removing data from the warehouse context. Users also cite workbook performance issues, advanced-feature complexity, limited visual customization, and some database compatibility gaps. ### What Do G2 Reviewers Say About Sigma? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Sigma, making it simple to learn and set up without extensive training. - Users value the **easy integration and intuitive interface** of Sigma, enhancing data accessibility and collaboration effectively. - Users commend the **excellent customer support** from Sigma, finding them responsive and knowledgeable for all inquiries. - Users find Sigma's **data visualization capabilities** essential for creating critical dashboards and simplifying data processing. - Users appreciate the **ease of data aggregation** with Sigma, streamlining processing and visualization for daily projects. **Cons:** - Users often experience **slow loading times** , resulting in inefficiencies and frustration while using Sigma. - Users experience **slow performance** with Sigma, especially when handling large datasets or lacking strong staff support. - Users find **limited customization** options frustrating, hindering the creation of visual data presentations and layouts. - Users note a **steep learning curve** with Sigma, requiring guidance for initial dashboard creation and navigation. - Users note several **missing features** in Sigma, such as limited visualizations and slow performance with large datasets. #### Key Features - Reports Interface - Data Column Filtering - Big Data Services - Data Transformation - Connectors #### What Are Recent G2 Reviews of Sigma? **"[Sigma unlocks data value for our organization](https://www.g2.com/survey_responses/sigma-review-10895340)"** **Rating:** 5.0/5.0 stars *— Austin M.* [Read full review](https://www.g2.com/survey_responses/sigma-review-10895340) --- **"[Easiest BI Tool: Live Snowflake Data in a Spreadsheet-Like Experience](https://www.g2.com/survey_responses/sigma-review-12573150)"** **Rating:** 4.0/5.0 stars *— Keerthan P.* [Read full review](https://www.g2.com/survey_responses/sigma-review-12573150) --- #### What Are G2 Users Discussing About Sigma? - [What is Sigma used for?](https://www.g2.com/discussions/what-is-sigma-used-for) - 1 comment ### 15. [Coefficient](https://www.g2.com/products/coefficient/reviews) **Average Rating:** 4.7/5.0 **Total Reviews:** 184 **Product Description:** Coefficient is a new way to work with your company data better, faster, and more accurately without ever leaving your spreadsheet, integrating with the tools you already use. Install the Coefficient Excel or Google Sheets extension and use it in a new or existing sheet in seconds. Once installed, Coefficient lives as a sidebar companion so your company data is only a couple of clicks away at any time. Any data source that you work with is available directly in your Coefficient sidebar – such as Salesforce, HubSpot, Snowflake, NetSuite, QuickBooks, MySQL, and Looker – with the ability to consolidate your data from multiple systems into one spreadsheet. Use Coefficient filters to easily customize your imports to only work with the data you need, keeping your spreadsheets performant. Quickly go back anytime to add more data in the same report. Never rebuild the same analysis twice by keeping your data up to date with scheduled updates. And, use Coefficient alerts to trigger Slack or email messages anytime your spreadsheet updates. Now, you can turn your spreadsheet into the most flexible, powerful monitoring system across all of your company data. Say “goodbye” to manual data workflows and “hello” to connected spreadsheets. ### What Do G2 Reviewers Say About Coefficient? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Coefficient, enjoying its seamless integration and user-friendly setup. - Users appreciate the **seamless automation** of Coefficient, enhancing efficiency with effortless data integration and refreshing. - Users value the **seamless integrations** provided by Coefficient, enhancing efficiency and ease of use. - Users value the **time-saving features** of Coefficient, enabling quick data import and effortless refresh in one click. - Users love the **easy integrations** of Coefficient, simplifying data connections and enhancing productivity effortlessly. **Cons:** - Users find the **limited features** of Coefficient restrict functionality, especially concerning filtering and integration needs. - Users note the **feature limitations** of Coefficient, particularly the lack of bulk updates and multiple filter options. - Users face a **limitation on data processing** , as not all rows may be included in reports, affecting usability. - Users note the **missing features** in Coefficient, particularly the lack of certain connectors and bulk update options. - Users experience **integration issues** with Coefficient, particularly with Salesforce and data pulling, affecting overall efficiency. #### What Are Recent G2 Reviews of Coefficient? **"[Effortless Salesforce to Sheets Integration](https://www.g2.com/survey_responses/coefficient-review-12701723)"** **Rating:** 5.0/5.0 stars *— Ellen Dericks C.* [Read full review](https://www.g2.com/survey_responses/coefficient-review-12701723) --- **"[Effortless Scheduled Refreshes. Eliminates Manual Exports and Makes Revenue Data Actionable](https://www.g2.com/survey_responses/coefficient-review-12318636)"** **Rating:** 5.0/5.0 stars *— Jacob R.* [Read full review](https://www.g2.com/survey_responses/coefficient-review-12318636) --- ### 16. [SAP Analytics Cloud](https://www.g2.com/products/sap-analytics-cloud/reviews) **Average Rating:** 4.2/5.0 **Total Reviews:** 748 **Product Description:** 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. ### What Do G2 Reviewers Say About SAP Analytics Cloud? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of SAP Analytics Cloud, allowing quick data access and straightforward reporting. - Users value the **seamless integration** of SAP Analytics Cloud with other SAP systems, enhancing data analysis and planning efficiency. - Users value the **strong visualization capabilities** of SAP Analytics Cloud, enhancing storytelling and improving data communication with stakeholders. - Users value the **easy integrations** of SAP Analytics Cloud, enhancing collaboration and streamlining data management across systems. - Users value the **seamless integration** of SAP Analytics Cloud with SAP systems, enhancing analytics and planning capabilities. **Cons:** - Users experience **slow performance** with large datasets in SAP Analytics Cloud, affecting efficiency and usability. - Users note a **steep learning curve** for new users, making initial setup and advanced features challenging to grasp. - Users often face a **steep learning curve** with SAP Analytics Cloud, making it challenging for newcomers to navigate effectively. - Users face **performance issues** with SAP Analytics Cloud, particularly when handling large datasets and complex calculations. - Users experience **slower performance** with large datasets, impacting efficiency and usability in SAP Analytics Cloud. #### 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) --- **"[Powerful all-in-one analytics and planning tool](https://www.g2.com/survey_responses/sap-analytics-cloud-review-11882259)"** **Rating:** 5.0/5.0 stars *— Vusala J.* [Read full review](https://www.g2.com/survey_responses/sap-analytics-cloud-review-11882259) --- #### 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 ### 17. [HockeyStack](https://www.g2.com/products/hockeystack/reviews) **Average Rating:** 4.5/5.0 **Total Reviews:** 80 **Product Description:** HockeyStack learns your company’s winning pattern for revenue generation, then Revenue Agents execute that process across every rep and every deal. Key capabilities include: - Revenue Agents: autonomous, intelligent systems that continuously analyze all deal, account, and behavioral data to make decisions and take actions that drive revenue outcomes. - Rep Cockpit: A single interface where agent outputs are pre-computed, decisions surface one at a time, and internal actions are executed automatically - Manager View: Managers can see exactly where deals are deviating or where reps are diverging from ideal behavior, without extra meetings or review cycles - Atlas: A data foundation that captures causality across the entire buyer journey, ingesting signals from CRM, call recordings, ad platforms, sales engagement, web activity, and more - Blueprint: A multi-layer ML pipeline that identifies the exact behaviors and sequences that drive closed-won, then matches every live deal against that validated process and flags deviation in real time - Self-Improving Loop: Every rep action, dismissal, edit, and deal outcome feeds back into the Blueprint, so the system gets smarter on its own over time Achieve reduced rep variance, faster ramp time, and more accurate forecasts, with impact compounding as the system learns. Get started with HockeyStack today! ### What Do G2 Reviewers Say About HockeyStack? *AI-generated summary from verified user reviews* **Pros:** - Users value the **detailed and flexible insights** from HockeyStack that enhance campaign performance analysis and ROI evaluation. - Users value the **flexible and detailed analytics** of HockeyStack, gaining insightful data for effective marketing strategies. - Users value the **ease of use** of HockeyStack, praising its simple setup and quick integration with systems. - Users commend the **helpful support team** at HockeyStack for their thorough and timely responses to inquiries. - Users praise the **exceptional customer support** of HockeyStack for its thorough and timely assistance. **Cons:** - Users find the **learning curve steep** , especially for those unfamiliar with attribution tools, but support is available. - Users note a **steep learning curve** for building reports, though support and resources help ease the process. - Users note a **complexity** in HockeyStack that may require time and support to fully master its features. - Users find a **difficult learning curve** with HockeyStack, requiring time and effort to fully grasp its functionality. - Users find a steep **learning difficulty** with HockeyStack, requiring time and support to become proficient. #### What Are Recent G2 Reviews of HockeyStack? **"[Broad Capabilities, Some Complexity in Setup](https://www.g2.com/survey_responses/hockeystack-review-12701250)"** **Rating:** 4.0/5.0 stars *— Carmine M.* [Read full review](https://www.g2.com/survey_responses/hockeystack-review-12701250) --- **"[Promising Tool, Some Drawbacks](https://www.g2.com/survey_responses/hockeystack-review-12260402)"** **Rating:** 4.0/5.0 stars *— Verified User* [Read full review](https://www.g2.com/survey_responses/hockeystack-review-12260402) --- #### What Are G2 Users Discussing About HockeyStack? - [What is HockeyStack used for?](https://www.g2.com/discussions/what-is-hockeystack-used-for) ### 18. [Knowi](https://www.g2.com/products/knowi/reviews) **Average Rating:** 4.9/5.0 **Total Reviews:** 27 **Product Description:** Knowi is an end-to-end AI-powered analytics platform designed for modern data, enabling enterprises of all sizes to dramatically accelerate the journey from raw data to actionable insights. With native integration to virtually any data source—including SQL, NoSQL (MongoDB, Elasticsearch, InfluxDB), REST APIs, cloud databases, and documents—Knowi eliminates the need for complex data transformation processes required by alternative solutions. Data teams can integrate, blend, visualize, and analyze data from any source 10X faster, all within a single platform. They can then leverage AI to uncover insights, embed analytics into applications, share dashboards with business users, and automate reporting. ### What Do G2 Reviewers Say About Knowi? *AI-generated summary from verified user reviews* **Pros:** - Users commend Knowi's **exceptional customer support** , highlighting responsive teams that ensure a smooth onboarding and problem-solving experience. - Users commend Knowi for its **exceptional onboarding and responsive support** , significantly easing the transition to data analytics. - Users highlight the **exceptional AI-driven analytics** of Knowi, enhancing their reporting and dashboard capabilities significantly. - Users value the **automation features** of Knowi, drastically reducing manual work and simplifying data management. - Users love the **intuitive dashboarding features** of Knowi, making data management effortless and efficient. **Cons:** - Users find a significant **learning curve** with Knowi, particularly for advanced features and API integrations. - Users feel there is a **lack of guidance** for API connections, making initial setup with Knowi time-consuming. - Users feel a **lack of tutorials** for API connections makes initial setups with Knowi time-consuming and challenging. #### What Are Recent G2 Reviews of Knowi? **"[Chief Executive Officer](https://www.g2.com/survey_responses/knowi-review-12447928)"** **Rating:** 5.0/5.0 stars *— Paul N.* [Read full review](https://www.g2.com/survey_responses/knowi-review-12447928) --- **"[Intuitive Dashboarding with Exceptional Support](https://www.g2.com/survey_responses/knowi-review-12378559)"** **Rating:** 5.0/5.0 stars *— Jose D.* [Read full review](https://www.g2.com/survey_responses/knowi-review-12378559) --- ### 19. [Databricks](https://www.g2.com/products/databricks/reviews) **Average Rating:** 4.6/5.0 **Total Reviews:** 761 **Why buyers love it?:** What stood out to me in Databricks’ G2 feedback was how reviewers connect analytics, data engineering, and machine learning work in one governed workspace. Reviewers highlight Unity Catalog, lineage, incremental ingestion, notebook collaboration, Power BI integration, and natural-language assistance for querying datasets. The product reads as a strong fit when teams need large data workflows that support both BI and machine learning use cases. Users also cite operational complexity, performance tuning needs, migration effort, cost control concerns, and the need for skilled data teams. ### What Do G2 Reviewers Say About Databricks? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **ease of use and numerous features** of Databricks, enhancing their data processing and machine learning tasks. - Users praise the **ease of use** of Databricks, enhancing their overall experience with its intuitive interface. - Users appreciate the **seamless integrations** of Databricks, enhancing real-time processing and supporting various development languages. - Users value the **seamless collaboration** Databricks offers, enhancing teamwork on data projects with real-time insights. - Users value the **integrated analytical features** of Databricks, enhancing operations and providing comprehensive insights on technology. **Cons:** - Users note a significant **learning curve** with Databricks, particularly due to its complex permissions and compute modes. - Users find Databricks to be **expensive** , especially when handling large data, limiting its accessibility for some customers. - Users find the **steep learning curve** of Databricks challenging, particularly for those new to big data tools. - Users find the **complexity** of Databricks challenging, especially with advanced features and initial setup requirements. - Users experience a **complex setup** process initially, but support helps to simplify the experience over time. #### Key Features - Cloud - Data Lake - Spark Integration - Spark Integration - Workload Processing #### What Are Recent G2 Reviews of Databricks? **"[Databricks in my case: Multiple Integrations, Intuitive UI, and Reliable Performance](https://www.g2.com/survey_responses/databricks-review-12834055)"** **Rating:** 4.0/5.0 stars *— Yelnur K.* [Read full review](https://www.g2.com/survey_responses/databricks-review-12834055) --- **"[Lakebase - Good Option for Low Latency Data Serving with Databricks Integration](https://www.g2.com/survey_responses/databricks-review-12542177)"** **Rating:** 4.5/5.0 stars *— Senthil K.* [Read full review](https://www.g2.com/survey_responses/databricks-review-12542177) --- #### What Are G2 Users Discussing About Databricks? - [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments - [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments - [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 2 upvotes ### 20. [Equals](https://www.g2.com/products/equals/reviews) **Average Rating:** 4.8/5.0 **Total Reviews:** 39 **Product Description:** The next-generation spreadsheet. Equals is the fastest, most flexible way to measure and report on your SaaS business. Automate your reporting with precision. Analyze from the comfort of a spreadsheet. Powered by live data from Stripe, Salesforce, Hubspot, and your SQL database. ---- We all understand the power and value of data. Yet, amongst the explosion of new tools to help us make sense of it all, we invariably end up back in a spreadsheet. BI tools are inherently complex and one-size-fits-all solutions simply don't cut it. Why? The spreadsheet is the only tool that gives you the flexibility to match the specifics of your business. There's really nothing like it — a canvas on which you can play, move, touch, and feel data while building compounding, sophisticated analyses and reports. Yet, starting analyses in Excel and Sheets is painful. Your data always comes from somewhere else, you have to export it to a CSV, import it into your spreadsheet, and hope you didn't miss anything. And then keeping it up-to-date is the original pain times ten. At Equals, we're building a next-generation spreadsheet that works just like those that came before but is fit for this era of work. It's directly connected to your data and is as unconstrained and flexible as a spreadsheet. It's paired with BI-grade dashboards that are as quick and easy to create as a doc. Based in North America, we have been building software and companies for 10+ years at the likes of Intercom, Atlassian, Stripe, and Loom. We're backed by the best innovators and investors in Silicon Valley, including a16z and Craft Ventures. ### What Do G2 Reviewers Say About Equals? *AI-generated summary from verified user reviews* **Pros:** - Users love the **effortless ease of use** in Equals, making data tasks simple and effective with great support. - Users commend the **incredible customer support** from Equals, highlighting their responsiveness and valuable assistance throughout the setup process. - Users praise the **fast data analysis** capabilities of Equals, streamlining dashboard creation and overall convenience. - Users appreciate the **data manipulation capabilities** of Equals, allowing seamless analysis and dashboard building without exporting. - Users praise the **setup ease** of Equals, highlighting expert support that simplifies integration and data management. **Cons:** - Users experience **bugs like workbook crashes and date sorting issues** that detract from the overall functionality of Equals. - Users experience a **slight learning curve** with Equals, especially those new to the interface and its features. - Users are missing a crucial **filters feature** , despite ongoing development and frequent updates from the Equals team. - Users find the **complex usage** of Equals challenging, especially for those new to the product. - Users face **copy-paste issues** in Equals, impacting their workflow and convenience compared to Excel. #### What Are Recent G2 Reviews of Equals? **"[One of the best tools for GTM Teams](https://www.g2.com/survey_responses/equals-review-12316749)"** **Rating:** 5.0/5.0 stars *— Badr E.* [Read full review](https://www.g2.com/survey_responses/equals-review-12316749) --- **"[Effortless CRM Data Analysis and Dashboard Creation](https://www.g2.com/survey_responses/equals-review-12082723)"** **Rating:** 4.0/5.0 stars *— Appu M.* [Read full review](https://www.g2.com/survey_responses/equals-review-12082723) --- ### 21. [Domo](https://www.g2.com/products/domo/reviews) **Average Rating:** 4.3/5.0 **Total Reviews:** 987 **Why buyers love it?:** When I assessed Domo’s G2 feedback, reviewers consistently framed it as a central place for data, dashboards, and business visibility. Reviewers highlight easy setup, a user-friendly interface, Magic ETL, AI features, broad insights sharing, and accessibility for less technical users. The product reads as a fit for organizations that want to connect data sources and give business teams a direct path to dashboards and analysis. Users also mention credit usage concerns, pricing complexity, occasional bugs, limited SQL depth, and feature maturity issues. ### What Do G2 Reviewers Say About Domo? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Domo, highlighting its user-friendly interface and intuitive design. - Users value the **flexible dashboards** in Domo, enhancing data visualization and making it user-friendly and efficient. - Users praise Domo for its **intuitive design** , facilitating easy access and effective data management for all users. - Users praise **easy integrations** with Domo, enhancing data management and streamlining workflows across various platforms. - Users love Domo's **seamless integration capabilities** , enabling efficient data management from various sources for informed decision-making. **Cons:** - Users find that the **learning curve is steep** , needing extra attention to keep up with features and updates. - Users highlight the **missing features** in Domo, particularly the lack of flexibility and clarity in functionality. - Users face **data management issues** with Domo, including unreliable connectors and challenges in reporting and licensing. - Users find Domo to be **expensive** , especially with sudden price hikes and a confusing consumption model. - Users find Domo's **complexity** frustrating, citing rigidity and difficulties in making fast changes to datasets. #### Key Features - Steps to Answer - Data Column Filtering - Data Visualization - Data Modeling - Connectors #### What Are Recent G2 Reviews of Domo? **"[All-in-One Platform for Real-Time Analytics and Dashboards](https://www.g2.com/survey_responses/domo-review-12676104)"** **Rating:** 5.0/5.0 stars *— Anuj T.* [Read full review](https://www.g2.com/survey_responses/domo-review-12676104) --- **"[Comprehensive Analytics Tool with a Learning Curve](https://www.g2.com/survey_responses/domo-review-9326769)"** **Rating:** 5.0/5.0 stars *— John L.* [Read full review](https://www.g2.com/survey_responses/domo-review-9326769) --- #### 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) ### 22. [Strategy One (formerly MicroStrategy ONE)](https://www.g2.com/products/strategy-one-formerly-microstrategy-one/reviews) **Average Rating:** 4.2/5.0 **Total Reviews:** 529 **Product Description:** 🚀 Strategy One – the AI+BI Platform for Enterprise Analytics at Scale What is Strategy One? Strategy One is the enterprise AI + BI platform that powers data-driven decision-making at scale. Built for complex enterprises, it unifies business intelligence, advanced analytics, and governed data modeling into a single, open platform. With native AI-powered workflows, pixel-perfect dashboards, modern self-service tools, and seamless integrations with Excel, Power BI, and Tableau, Strategy One delivers trusted insights wherever decisions are made. Why Strategy One? Unlike fragmented BI stacks or limited legacy tools, Strategy One provides an end-to-end platform with one trusted semantic core. Business users get governed self-service. Analysts get powerful modeling tools. Executives get real-time answers they can trust. And IT retains full control over data access, definitions, and lineage. Whether you’re creating executive dashboards, deploying embedded analytics, scaling AI copilots, or consolidating BI tools—Strategy One meets the moment with: ✅ Cloud-native architecture ✅ Open integrations with 200+ data sources ✅ Enterprise-grade security and governance ✅ Industry-leading performance and scale ✅ Built-in support for AI copilots, agents, and models Strategy One is trusted by global enterprises in banking, retail, healthcare, and government to turn data into decisions—fast, securely, and at scale. ### What Do G2 Reviewers Say About Strategy One (formerly MicroStrategy ONE)? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Strategy One, enabling efficient data insights and visualization tools. - Users admire the **ongoing commitment to innovation** of Strategy One, enhancing capabilities and keeping the platform ahead. - Users find the **easy setup** of Strategy One effective, simplifying the onboarding process and enhancing usability. - Users appreciate the **customization options** in Strategy One, enhancing report building and dashboard creation efficiency. - Users appreciate the **flexible dashboard customization** of Strategy One, facilitating easy data access and comprehensive insights. **Cons:** - Users find a **steep learning difficulty** in Strategy One, often feeling overwhelmed and seeking clearer training focus. - Users find the **steep learning curve** of Strategy One challenging, making initial navigation feel overwhelming. - Users note the **missing features** in Strategy One, particularly in integration capabilities with tools like Copilot. - Users find the **complex usage** of Strategy One overwhelming initially, with a steep learning curve and integration challenges. - Users find **access restrictions** limiting, requiring an enterprise version for availability and customization options. #### What Are Recent G2 Reviews of Strategy One (formerly MicroStrategy ONE)? **"[Scalable, Enterprise-Ready BI with Strong Governance and Reliable Performance](https://www.g2.com/survey_responses/strategy-one-formerly-microstrategy-one-review-12406962)"** **Rating:** 5.0/5.0 stars *— Carlos G.* [Read full review](https://www.g2.com/survey_responses/strategy-one-formerly-microstrategy-one-review-12406962) --- **"[Empowers Data Accessibility, with Minor Transition Hiccups](https://www.g2.com/survey_responses/strategy-one-formerly-microstrategy-one-review-12417688)"** **Rating:** 4.0/5.0 stars *— Van V. T.* [Read full review](https://www.g2.com/survey_responses/strategy-one-formerly-microstrategy-one-review-12417688) --- #### What Are G2 Users Discussing About Strategy One (formerly MicroStrategy ONE)? - [What is MicroStrategy used for?](https://www.g2.com/discussions/what-is-microstrategy-used-for) - [What is the difference between tableau and MicroStrategy?](https://www.g2.com/discussions/what-is-the-difference-between-tableau-and-microstrategy) - [How much does MicroStrategy cost?](https://www.g2.com/discussions/how-much-does-microstrategy-cost) - 1 comment ### 23. [Cube](https://www.g2.com/products/cube-2023-07-31/reviews) **Average Rating:** 4.5/5.0 **Total Reviews:** 27 **Product Description:** Cube Cloud is a universal semantic layer that makes it easy to connect siloed data and create consistent metrics that are accessible to any data consumer–AI, BI, spreadsheets, and embedded analytics. The solution provides unmatched integrations and interoperability, supporting a robust set of deployment options, data connectivity, coding languages, and native APIs so that you can build solutions to fit your unique requirements on the modern data stack. With Cube Cloud, business data becomes consistent, accurate, easy to access, and most importantly, trusted. Data engineers and application developers use Cube Cloud’s code-first, developer-oriented platform to: - Organize and govern data from cloud data warehouses into centralized, consistent, and reusable data models and business definitions. - Apply software engineering best practices and processes to data management: CI/CD, isolated environments, and version control with Git integration. - Use intelligent capabilities like data model code generation and front-end embedded analytics code generation to increase productivity. - Optimize query performance and save on cloud data usage with pre-aggregation caching capabilities. - Deliver data to any downstream tool via data APIs: SQL, REST, GraphQL, AI, and MDX. Cube accelerates trusted data-driven decisions, delivering better experiences to employees inside the organization, customers outside the organization, and even machines with our native OpenAI integrations. Build Generative AI experiences with the AI API. For internal BI use cases, Cube Cloud provides a semantic catalog and Generative AI capabilities to simplify discovery, exploration, and access to modeled data and downstream, connected BI content for data analysts and business users. You can add unlimited named user accounts to allow anyone to search and reuse trusted data products and perform natural language queries in a simplified, business user-friendly interface. ### What Do G2 Reviewers Say About Cube? *AI-generated summary from verified user reviews* **Pros:** - Users find Cube exceptionally **easy to set up and maintain** , greatly reducing development efforts for small teams. - Users value the **flexibility and customization** of Cube, enhancing their embedded analytical applications effortlessly. - Users value the **powerful BI capabilities** of Cube, enabling complex metrics and scalable data solutions efficiently. - Users commend the **responsive customer support** of Cube, noting quick and proactive assistance that enhances the experience. - Users love the **flexibility** of CubeJS, enabling seamless integration and customization for data applications. **Cons:** - Users note the **missing features** in Cube, particularly regarding BI tool integrations and flexibility in metric creation. - Users report experiencing **significant bugs** with scaling and pre-aggregations, impacting overall reliability and usability. - Users find **data integration challenging** with BI tools, citing query issues and limited features compared to other platforms. - Users find Cube to have **limited features** , lacking comprehensive tools for documentation, visualization, and API support. - Users report issues with **software bugs** , including confusing pre-aggregations and syntax errors leading to integration challenges. #### What Are Recent G2 Reviews of Cube? **"[Great for AI applications and general data apps!](https://www.g2.com/survey_responses/cube-review-10751001)"** **Rating:** 4.5/5.0 stars *— Verified User in Commercial Real Estate* [Read full review](https://www.g2.com/survey_responses/cube-review-10751001) --- **"[Super Easy Access to the DEV team](https://www.g2.com/survey_responses/cube-review-11700913)"** **Rating:** 5.0/5.0 stars *— Verified User in Real Estate* [Read full review](https://www.g2.com/survey_responses/cube-review-11700913) --- ### 24. [Bold BI](https://www.g2.com/products/bold-bi/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 88 **Product Description:** Bold BI® by Syncfusion® is a modern, flexible analytics platform that empowers everyone—from business users to developers—to turn raw data into meaningful insights, fast. Whether you're embedding analytics into your application or building dashboards from scratch, Bold BI makes it easy to deliver powerful, interactive data experiences without compromising on performance or security. With an intuitive no-code, drag-and-drop interface, even non-technical users can create stunning dashboards in minutes. Meanwhile, developers enjoy deep customization through robust APIs, SDKs, and white-labeling options, making it simple to integrate analytics seamlessly into any application. With support for 130+ data sources, including Microsoft SQL Server, Azure SQL Data Warehouse, Oracle, REST APIs, Bold Datahub, and more, Bold BI offers unmatched data flexibility and connectivity. Designed for secure, scalable deployments, the platform’s multi-tenant architecture and enterprise-grade security features single sign-on (SSO) via OAuth2 and OpenID and role-based access control to ensure data protection and simplified user management. Real-time dashboard sharing, scheduled alerts, and export options make collaboration effortless, helping teams stay aligned and make faster, data-driven decisions. Backed by Syncfusion, Bold BI offers end-to-end expert support, ideal for organizations looking to scale their analytics. Customers benefit from 24/5 assistance through free scheduled support calls, live chat, and email—from onboarding to full implementation. NOTE: Older reviews may reference the historical product name, "Syncfusion Dashboard Platform." ### What Do G2 Reviewers Say About Bold BI? *AI-generated summary from verified user reviews* **Pros:** - Users commend the **exceptional customer support** from Bold BI, noting prompt responses and effective problem resolution. - Users find Bold BI's **ease of use** exceptional, with intuitive design and seamless integration for all skill levels. - Users value the **ease of integration** of Bold BI, facilitating seamless connections with various data sources. - Users love the **dashboard customization** features of Bold BI, enabling impressive and user-friendly analytics integration. - Users value the **seamless embedding capabilities** of Bold BI, enhancing their customer-facing dashboard experiences effortlessly. **Cons:** - Users report numerous **bugs** and issues during updates, impacting the overall functionality and user experience of Bold BI. - Users experience a **steep learning curve** with Bold BI, requiring technical knowledge and extensive documentation for advanced features. - Users find the **difficult setup** of Bold BI time-consuming, requiring tutorials and technical knowledge to navigate first time. - Users report experiencing numerous **software bugs** , especially with non-Windows versions, impacting overall usability and performance. - Users face challenges with **dashboard issues** , including complex setups, manual tweaks, and performance concerns on intricate layouts. #### What Are Recent G2 Reviews of Bold BI? **"[Powerful, Flexible Analytics Platform with Intuitive Design and Excellent Support](https://www.g2.com/survey_responses/bold-bi-review-12016141)"** **Rating:** 5.0/5.0 stars *— Mohamed zulfadli A.* [Read full review](https://www.g2.com/survey_responses/bold-bi-review-12016141) --- **"[Simple, Powerful, and Works Well](https://www.g2.com/survey_responses/bold-bi-review-10818671)"** **Rating:** 5.0/5.0 stars *— muhdin m.* [Read full review](https://www.g2.com/survey_responses/bold-bi-review-10818671) --- #### What Are G2 Users Discussing About Bold BI? - [What is Bold BI used for?](https://www.g2.com/discussions/what-is-bold-bi-used-for) - [What are Microsoft BI tools?](https://www.g2.com/discussions/what-are-microsoft-bi-tools) - [What are examples of BI tools?](https://www.g2.com/discussions/bold-bi-what-are-examples-of-bi-tools) ### 25. [Dataiku](https://www.g2.com/products/dataiku/reviews) **Average Rating:** 4.4/5.0 **Total Reviews:** 187 **Product Description:** Dataiku is the Platform for AI Success that unites people, orchestration, and governance to turn AI investments into measurable business outcomes. It helps organizations move from fragmented experimentation to coordinated, trusted execution at scale. Built for AI success: Dataiku brings business experts and AI specialists into the same environment, embedding business context into analytics, models, and AI agents. Business teams can self-serve and innovate, while AI experts build, deploy, and optimize quickly, closing the gap between pilots and production. Orchestration that scales: Dataiku connects data, AI services, and enterprise apps across analytics, machine learning, and AI agents. Integrated workflows deliver value across any cloud or infrastructure without vendor lock-in or fragmentation. Governance you can trust: Dataiku embeds governance across the AI lifecycle, enabling teams to track performance, cost, and risk to keep systems explainable, compliant, and auditable. ### What Do G2 Reviewers Say About Dataiku? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **user-friendly learning resources** in Dataiku, enabling quick mastery and streamlined machine learning development. - Users find Dataiku's **ease of use** invaluable for simplifying ML development and streamlining data extraction processes. - Users appreciate the **user-friendly interface** of Dataiku, making it easy for all team members to collaborate effectively. - Users find **easy integrations** with Dataiku enhances flexibility and simplifies workflows across various platforms. - Users value the **productivity improvements** from Dataiku's unified platform, enhancing data management and decision-making efficiency. **Cons:** - Users find the **learning curve steep** , especially for advanced features that require deeper technical knowledge and understanding. - Users find the **steep learning curve** challenging for beginners, making it difficult to fully utilize Dataiku's capabilities. - Users find the **difficult learning curve** in Dataiku challenging, especially for advanced features and keeping up with updates. - Users experience **slow performance** in Dataiku, especially with large datasets and complex scenarios, impacting analytics efficiency. - Users find the **expensive pricing structure** a barrier, especially limiting for smaller companies and teams. #### What Are Recent G2 Reviews of Dataiku? **"[Dataiku:A plug in tool for Data Science](https://www.g2.com/survey_responses/dataiku-review-8032719)"** **Rating:** 4.5/5.0 stars *— Rakshith N.* [Read full review](https://www.g2.com/survey_responses/dataiku-review-8032719) --- **"[Dataiku Speeds Up Repeatable Marketing Data Workflows](https://www.g2.com/survey_responses/dataiku-review-12858707)"** **Rating:** 4.5/5.0 stars *— Michele C.* [Read full review](https://www.g2.com/survey_responses/dataiku-review-12858707) --- #### What Are G2 Users Discussing About Dataiku? - [Is Dataiku an ETL tool?](https://www.g2.com/discussions/is-dataiku-an-etl-tool) - [Is Dataiku web based?](https://www.g2.com/discussions/is-dataiku-web-based) - [What is DSS Dataiku?](https://www.g2.com/discussions/what-is-dss-dataiku) ## What Is Analytics Platforms? [Analytics Tools & Software](https://www.g2.com/categories/analytics-tools-software) ## What Software Categories Are Similar to Analytics Platforms? - [Data Visualization Tools](https://www.g2.com/categories/data-visualization-tools) - [Predictive Analytics Software](https://www.g2.com/categories/predictive-analytics) - [Embedded Business Intelligence Software](https://www.g2.com/categories/embedded-business-intelligence) --- ## How Do You Choose the Right Analytics Platforms? ### What You Should Know About Analytics Platforms ### What are analytics software platforms? Analytics platforms, also known as business intelligence (BI) platforms, enable companies to gain visibility into their data through data integration, cleansing, blending, enrichment, discovery, and more. These tools are robust systems that sometimes require IT and data science skills to access and decipher company data through custom queries.  Analytics platforms offer a comprehensive look into a company’s data by pulling from structured and unstructured data sources through detailed queries. Casual business users also benefit from analytics platforms, which offer customizable dashboards and the ability to drill into particular data points and trends. ### What types of analytics tools and platforms exist? #### **All-in-one software** ##### **Self-service analytics platforms** Self-service analytics platforms do not require coding knowledge, so business end users can use them for data needs. Cloud-based business analytics software often provides drag-and-drop functionality for building dashboards, prebuilt templates for querying data, and, occasionally, natural language querying for data discovery.  ##### **Embedded BI software** Embedded BI software can integrate proprietary analytics functionality within other business applications. Businesses may choose an embedded product to promote user adoption; by placing the analytics inside regularly used software, companies enable employees to take advantage of available data. These solutions provide self-service functionality so average business end users can use data for improved decision-making. #### **Point solutions** ##### **Root cause analysis** Companies of all sizes produce vast amounts of data from a host of different sources. It can be difficult to keep track of the ebbs and flows of data and to spot outliers and trends across tens if not hundreds (sometimes even thousands) of data sources. Some solutions provide the user with a bird' s-eye view of their data and intelligently alert them to changes in real time. Once alerted, they are able to dive in to evaluate the situation and solve it. ### What are the common features of analytics solutions? Analytics software platforms are a great aid to any organization needing timely data visualization of high-level analytics. The following are some core features within analytics platforms that can help users make the most of them: **Data preparation:**  Although standalone [data preparation software](https://www.g2.com/categories/data-preparation) exists that assists in discovering, blending, combining, cleansing, and enriching data—so large datasets can be easily integrated, consumed, and analyzed—analytics platforms must incorporate these functionalities into their core offering. In particular, analytics platforms must support data blending and modeling, allowing the end user to combine data across different databases and other data sources and to develop robust data models of this data. This is a critical step in making meaning out of the chaos by combining data from various sources. **Data management:** Once the data is properly integrated, it must be managed. This includes restricting data access to certain users, for example. Although some companies opt for a standalone data management solution, such as a data warehouse, analytics platforms must, by definition, provide some level of data management. **Data modeling and blending:** As mentioned, it is not efficient and often not effective to examine data when it is sprawled across many systems. As a business cloud, analytics platforms help businesses consolidate data and combine data points to understand the relationship between data and derive deep insights. **Reports and dashboards:** Multilayered, real-time dashboards are a central feature of analytics platforms. Users can program their analytics software to display metrics of their choice and create multiple dashboards that show analytics related to specific teams or initiatives. From predictive website traffic analytics to customer conversion rates over a specified period, users can choose their preferred metrics to feature in dashboards and create as many dashboards as necessary.  Administrators can adjust the permissions of different dashboards so they are accessible to the users in the company who need them the most. Users can share specific dashboards on office monitors or take screengrabs of dashboards to save and share as needed. Some analytics platform products may allow users to explore dashboards on their mobile devices. [**Self service**](https://www.g2.com/categories/analytics-platforms/f/self-service) **:** Organizations use these tools to build interactive dashboards for discovering actionable insights. This enables business users like sales representatives, human resource managers, marketers, and other non-data team members to make decisions based on relevant business data. **Advanced analytics:** Many analytics solutions are incorporating advanced features, sometimes called augmented analytics, to better understand a business’s data, even without IT support. These can include predictive analytics capabilities and data discovery, which includes intelligent suggestions for data visualization and machine learning-powered suggestions for deeper insights. Other features include [Anomaly detection](https://www.g2.com/categories/analytics-platforms/f/anomaly-detection), [Query based](https://www.g2.com/categories/analytics-platforms/f/query-based), [Search](https://www.g2.com/categories/analytics-platforms/f/search), [Traditional](https://www.g2.com/categories/analytics-platforms/f/traditional) ### What are the benefits of using analytics platforms? **Replace old or disparate software:** Businesses can replace outdated data storage solutions and reporting tools and migrate to an all-inclusive business cloud as an analytics platform. However, data migration is not essential for deploying an analytics solution, as businesses may not have the time or resources to do so. Therefore, it should be noted that these platforms can integrate with a whole host of solutions, such as [enterprise resource planning (ERP)](https://www.g2.com/categories/erp-systems) and [customer relationship management (CRM) software](https://www.g2.com/categories/crm). **Improve productivity:** The days of sorting through tens, if not hundreds, of systems and needing immense support from IT have passed. With analytics platforms (especially those that are self-service and have features such as natural language search), anyone looking for data and data analysis, including average business users, can derive insights from their data. **Save time (automation):** For most analytics platforms, users no longer need a strong background in query languages. Instead, data discovery and root cause analysis allow users to automatically receive alerts and insights into their data and get notified if the data has changed meaningfully. **Reduce errors:** Although standalone data preparation tools may be the right solution for businesses with particularly complex data, analytics platforms allow users to clean and prepare their data through data mapping and deduplication methods. **Consolidate data:** In this data-driven era, essentially every program and device a business has produces massive data. To understand this diverse data in the best way possible, combining it through methods such as data blending, which allows users to integrate data from multiple sources into a functioning dataset, is often necessary. **Improve processes:** Without an analytics platform to be used across a business, processes can be slow and inefficient as interested parties seek data from disparate sources and request data from various people. Analytics platforms can help a business user quickly access data and data analysis and share it with internal and external stakeholders. ### **Who uses analytics tools?** Analytics platforms can have both internal and external users.  #### **Internal users** **Data analysts and data scientists:** These employees are generally the power users of analytics tools, creating complex queries inside the platforms to gather a deeper understanding of business-critical data. These teams may also be tasked with building self-service dashboards to distribute to other teams. **Sales teams:** Sales teams use self-service analytics tools and embedded analytics solutions to obtain insights into prospective accounts, sales performance, and pipeline forecasting, among many other use cases. Using analytics tools in a sales team can help businesses optimize their sales processes and influence revenue. **Marketing teams:** Marketing teams often run different types of campaigns, including email marketing, digital advertising, or even traditional advertising campaigns. Analytics tools allow marketing teams to track the performance of those campaigns in one central location. **Finance teams:** Finance teams leverage analytics software to gain insight into the factors impacting an organization's bottom line. By integrating financial data with sales, marketing, and other operations data, accounting and finance teams pull actionable insights that might not have been uncovered using traditional tools. **Operations and supply chain teams:** Analytics solutions often utilize a company's ERP system as a data source. These applications track everything from accounting to supply chain and distribution; supply chain managers can optimize several processes to save time and resources by inputting supply chain data into an analytics platform.  #### **External users** **Consultants:** Businesses, especially larger ones, do not always understand the breadth and depth of their data, perhaps not even knowing where to begin. An external consultant wielding a powerful analytics platform can help businesses better understand their data and, as a result, make more informed business decisions.  Users may consider contacting [BI consulting partners](https://www.g2.com/categories/business-intelligence-bi-consulting) to help determine the most relevant analytics and data to capture about their company’s overall success. Following a proper consultation, these agencies may offer assistance with setting up or choosing BI tools. A number of these agencies can assist businesses with the entire BI process, from complete data analysis to the shaping of processes or protocols related to data collection. A relationship with these consultants can prove highly beneficial for users who have never performed data analysis before or want to optimize their company’s reporting. **Partners:** Partnerships between companies often involve data sharing and cross-company collaboration. As a result, a centralized repository of data, which would allow for data management, data querying, and data insights, can provide an essential tool for these businesses to succeed together, providing them with a birds-eye view of their data. ### **What are the alternatives to analytics platforms?** Alternatives to analytics platforms can replace this type of software, either partially or completely: [**Marketing analytics software**](https://www.g2.com/categories/marketing-analytics) **:** Businesses looking for tools geared toward marketing use cases and marketing data (e.g., related to targeting prospects) should look at marketing analytics solutions that are purpose-built for this. [**Sales analytics software**](https://www.g2.com/categories/sales-analytics) **:** Although sales data such as revenue forecasts and closed deals can be imported and analyzed in general-purpose analytics platforms, sales analytics platforms can provide a more granular analysis of sales-related data and might have better integrations with sales tools such as CRMs.  [**Log analysis software**](https://www.g2.com/categories/log-analysis) **:**  If a business wants to focus on analyzing its log data from applications and systems, it could benefit from log analysis software, which helps enable the documentation of application log files for records and analytics. [**Predictive analytics software**](https://www.g2.com/categories/predictive-analytics) **:** Broad-purpose analytics platforms allow businesses to conduct various forms of analysis, such as prescriptive, descriptive, and predictive. Since analytics platforms allow for these different types of analyses, they might not provide the most robust features for any type. Therefore, businesses focused on looking at past and present data to predict future outcomes can use predictive analytics software for a more fine-tuned solution.  [**Text analysis software**](https://www.g2.com/categories/text-analysis) **:** Analytics platforms are focused on structured or numerical data, allowing users to drill down and dig into numbers to inform business decisions. Text analysis solutions are the best bet if the user is looking to focus on unstructured or text data. These tools help users quickly understand and pull sentiment analysis, key phrases, themes, and other insights from unstructured text data. [**Data visualization software**](https://www.g2.com/categories/data-visualization) **:** Data visualization tools can be an excellent place for businesses to start when looking to better understand their data. With capabilities including dashboards and reporting, data visualization software can often be quick and easy to set up and is frequently cheaper than more robust analytics platforms.  However, it is essential to recognize their limitations. Data visualization solutions do what they say on the box: visualization. They do not give the user an end-to-end analytics solution from data preparation to data insights, nor do they provide significant data management capabilities. ### **Software and services related to analytics platforms** Related solutions that can be used together with analytics platforms include: [**Embedded business intelligence software**](https://www.g2.com/categories/embedded-business-intelligence) **:** Analytics platforms are standalone platforms that help companies analyze data. Businesses who want to build analytics capabilities into applications, whether that be for internal or external use, can use embedded BI software to accomplish this goal. [**Database software**](https://www.g2.com/categories/database-software) **:** There are a plethora of solutions for storing, organizing, and sharing large amounts of data that can later be accessed and analyzed by analytics tools. Database software includes everything from [big data software](https://www.g2.com/categories/big-data) to traditional table-based [relational databases](https://www.g2.com/categories/relational-databases). Businesses should research and implement whichever database tools make the most sense for their particular data types or analytical needs.  When considering an analytics solution, users should investigate which databases can integrate with the tool to make the most logical product choice for their situation. Analytics products would not serve much purpose without one or more company databases to pull data from when the time comes. ### Challenges with analytics platforms **Configuration:** Analytics solutions may have a highly technical setup process, requiring IT or developmental expertise. When trying to implement one of these platforms without an in-house data scientist or IT professional, users may struggle with getting the technology off the ground, integrating it with the appropriate solutions, and creating queries for data collection. This could mean a significant loss of resources and an inability to use the tool as intended. Users can contact BI consulting providers for assistance setting up a program or, in some cases, for handling the entirety of BI reporting. **Overreliance:** Focusing too much on data and analytics can also be problematic. Data-driven decisions are critical to a business’s success, but data-only decisions ignore the various voices from within and without the organization. Successful companies combine rigorous analytics with anecdotal storytelling and thoughtful conversations about the business's success and components. **Integrations:** If the analytics tool does not fully integrate with existing software, getting a complete view of a business’s operational performance becomes challenging. Similarly, if an integration experiences a communication error or other issue during a data query, it causes an incorrect or incomplete reading. Users should make a point to monitor these connections and any potential performance issues throughout their software stack to ensure that correct, complete, and up-to-date information is being processed and displayed on dashboards. **Data security:** Companies must consider security options to ensure the right users see the correct data and guarantee strict data security. Effective analytics solutions should offer security options that enable administrators to assign verified users different levels of access to the platform based on their security clearance or level of seniority. ### How to choose the best analytics tools #### Requirements Gathering (RFI/RFP) for Analytics Platforms If a company is just starting and looking to purchase the first analytics platform, or maybe an organization needs to update a legacy system--wherever a business is in its buying process, g2.com can help select the best analytics platform. The particular business pain points might be related to all the manual work that must be completed. If the company has amassed a lot of data, it needs to look for a solution that can grow with the organization. Users should think about the pain points and jot them down; these should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees needing this software, as this drives the number of licenses they will likely buy. Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist is a detailed guide with necessary and nice-to-have features, including budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more. Depending on the deployment scope, producing an RFI, a one-page list with a few bullet points describing what is needed from an analytics platform might be helpful. #### Compare Analytics Platforms Products **Create a long list** From meeting the business functionality needs to implementation, vendor evaluations are essential to the software buying process. For ease of comparison, after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor. **Create a short list** From the long list of vendors, it is helpful to narrow the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list, businesses can produce a matrix to compare the features and pricing of the various solutions. **Conduct demos** To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.  #### Selection of analytics platforms **Choose a selection team** Before getting started, creating a winning team that will work together throughout the process, from identifying pain points to implementation, is crucial. The software selection team should consist of organization members with the right interests, skills, and time to participate in this process. A good starting point is to aim for three to five people who fill roles such as the primary decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator, or security administrator. The vendor selection team may be more minor in smaller companies, with fewer participants, multitasking, and taking on more responsibilities. **Analyze the data** As analytics platforms are all about the data, the user must ensure that the selection process is also data-driven. The selection team should compare notes and facts and figures that they noted during the process, such as time to insight, number of visualizations, and availability of advanced analytics capabilities. **Negotiation** Just because something is written on a company’s pricing page does not mean it is gospel (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to discount multiyear contracts or recommend the product to others. **Final decision** After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and received, the buyer can be confident that the selection was correct. If not, it might be time to return to the drawing board. ### How much do analytics software platforms cost? As mentioned above, analytics platforms come as both on-premises and cloud solutions. Pricing between the two might differ, with the former often coming with more upfront costs for setting up the infrastructure.  As with any software, analytics platforms are frequently available in different tiers, with the more entry-level solutions costing less than the enterprise-scale ones. The former will often not have as many features and may have caps on usage. Vendors may have tiered pricing, in which the price is tailored to the users’ company size, the number of users, or both. This pricing strategy may come with some support, which might be unlimited or capped at a certain number of hours per billing cycle. Once set up, analytics platforms, especially those deployed in the cloud, do not often require significant maintenance costs. As these platforms often come with many additional features, businesses looking to maximize the value of their software can contract third-party consultants to help them derive insights from their data and get the most out of the software. #### Return on Investment (ROI) Businesses deploy analytics platforms to derive a return on investment (ROI). As they are looking to recoup the losses they spent on the software, it is critical to understand its costs. As mentioned above, analytics platforms are typically billed per user, sometimes tiered, depending on the company size. More users will generally translate into more licenses, which means more money. Users must consider how much is spent and compare that to what is gained in terms of efficiency and revenue. Therefore, businesses can compare processes between pre- and post-deployment software to understand better how processes have been improved and how much time has been saved. They can even produce a case study (either for internal or external purposes) to demonstrate the gains they have seen from using an analytics tool. ### Implementation of analytics software solutions **How are analytics software Implemented?** Implementation differs drastically depending on the complexity and scale of the data. In organizations with vast amounts of data in disparate sources (e.g., applications, databases, etc.), it is often wise to utilize an external party, whether an implementation specialist from the vendor or a third-party consultancy. With vast experience under their belts, they can help businesses understand how to connect and consolidate their data sources and use the software efficiently and effectively. **Who is responsible for analytics platform implementation?** Properly deploying an analytics platform may require many people or teams. This is because, as mentioned, data can cut across teams and functions. As a result, one person or even one team rarely has a complete understanding of all of a company’s data assets. With a cross-functional team, a business can begin to piece together its data and begin the analytics journey, starting with proper data preparation and management. ### Emerging trends related to analytics platforms **Increase data accessibility** Business data is no longer locked up in silos. With analytics platforms, more users across a business can find, access, and analyze this data. In addition, [artificial intelligence (AI) tools](https://www.g2.com/categories/artificial-intelligence) such as [natural language processing (NLP) software](https://www.g2.com/categories/natural-language-processing-nlp) help make searching through and for data more accessible and powerful, providing more accurate results. With the amount of data accessible to businesses today, it is a near necessity that they implement some type of analytics software to understand and act on that data better. Implementing analytics software has been a significant initiative for companies undergoing digital transformation, as these tools offer deeper visibility into an organization's data. Companies adopt these solutions to make sense of large datasets collected from various sources. **Shift from on-premises to cloud** The move from on-premises data analytics to the cloud has been underway for several years, with more and more businesses moving their data and data insights into the cloud. This is taking place for various reasons, such as time to insight. Moving away from on-premises infrastructure has helped many companies enable data work anywhere one has access to the cloud—anywhere with internet access. However, not all data users have the luxury of working in the cloud for several reasons, including data security and issues related to latency. In industries such as health care, strict regulations such as the [Health Insurance Portability and Accountability Act (HIPAA)](https://learn.g2.com/health-insurance-portability-and-accountability-act) require data to be secure. Although it is possible to ensure this security in the cloud, it can be more complicated. **Conversational AI** Historically, to query data within an analytics solution, users needed to master a query language like SQL. With the rise of conversational interfaces, users uncover the data and insights they seek using intuitive language. Intuitive methods of querying data enable a larger user base to access and make sense of company data. **Machine learning** AI is quickly becoming a promising feature of analytics solutions throughout the data journey, from ingestion to insights. From AI-powered data preparation to smart insights, in which the platform suggests visualizations to the end user, analytics platforms are quickly becoming more powerful. Machine learning is helping end users discover hidden insights, allowing them to make sense of data and understand what they are seeing.