Best Enterprise Analytics Platforms

How Many Analytics Platforms Products Does G2 Track?

Total Products under this Category: 592

Category Stats (Sep 2026)

  • Average Rating: 4.51/5 (↑0.01 vs Aug 2026) The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: BlazeSQL (+2.75%) - Among all products in this category, BlazeSQL recorded the largest rating increase compared to last month

Last updated: September 01, 2026

How Does G2 Rank Analytics Platforms Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 29,000+ Authentic Reviews
  • 592+ 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.

G2 Grid® for Analytics Platforms

G2 Grid® for Analytics Platforms plotting products by satisfaction and market presence

Highlighted products: Tableau, Microsoft Power BI, Databricks, Alteryx, Oracle Analytics Cloud, Kyvos Semantic Layer, IBM Cognos Analytics, and SAS Viya.

Underlying data: [Grid® JSON](https://www.g2.com/categories/analytics-platforms/grids.json?focus%5B%5D=tableau&focus%5B%5D=microsoft-microsoft-power-bi&focus%5B%5D=databricks&focus%5B%5D=alteryx&focus%5B%5D=oracle-analytics-cloud&focus%5B%5D=kyvos-semantic-layer&focus%5B%5D=ibm-cognos-analytics&focus%5B%5D=sas-sas-viya&segment=enterprise)

Tableau

Tableau is the world’s leading AI-powered analytics platform. Whether you are a business user or an analyst, Tableau turns trusted data into actionable insights. With our flexible, interoperable platform, you can: Turn data into action at scale with human and agent collaboration. Tableau Next delivers agentic AI for faster data-insight-action workflows. It surfaces insights, provides proactive recommendations, and helps you take action in the flow of work. Scale data-driven insights with complete operational confidence. Tableau Cloud enables fully managed analytics at scale. It accelerates your time to value and gives you access to the latest AI-powered innovations. Deploy visual, self-service analytics with unmatched control and flexibility. Tableau Server meets your organization's governance and security needs. It provides enterprise-grade, self-service analytics on-premise or in your private cloud.

Average Rating: 4.4/5.0

Total Reviews: 3,685

How Do G2 Users Rate Tableau?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.3/10 (Category avg: 8.4/10)
  • Reports Interface: 8.7/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.5/10 (Category avg: 8.5/10)

Who Is the Company Behind Tableau?

  • Seller: Salesforce
  • Company Website:
  • Year Founded: 1999
  • HQ Location: San Francisco, CA
  • Twitter: @salesforce
    579,511 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    89,711 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Business Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 41% Large, 36% Medium

What Do G2 Reviewers Say About Tableau?

AI-generated summary from verified user reviews

Pros
  • Users highlight the ease of use of Tableau, simplifying data visualization and integration for effective decision-making.
  • Users value the ease of creating interactive visualizations with Tableau, simplifying data analysis from multiple sources.
  • Users love the intuitive and powerful visualization capabilities of Tableau, enabling clear insights from complex data.
  • Users appreciate the ease of use and powerful visualization features of Tableau, streamlining data presentation and analysis.
  • Users find Tableau's intuitive design exceptional, enabling effortless data visualization and interactive dashboards for effective reporting.
Cons
  • Users find the learning curve steep, complicating the onboarding process and integration with Salesforce.
  • Users find learning Tableau challenging, particularly due to its complexity and difficulties in collaboration and calculations.
  • Users find Tableau expensive, with costs complicating its value in large organizations and advanced functionalities.
  • Users experience slow performance with large datasets and lengthy data refresh processes, leading to frustration.
  • Users find Tableau's onboarding complex, making simple tasks unnecessarily complicated and challenging to switch from MS products.

What Are Recent G2 Reviews of Tableau?

What Are G2 Users Discussing About Tableau?

Microsoft Power BI

Power BI Desktop puts visual analytics at your fingertips. With this powerful authoring tool, you can create interactive data visualizations and reports. Connect, mash up, model, and visualize your data. Place visuals exactly where you want them, analyze and explore your data, and share content with others by publishing to the Power BI web service. Power BI Desktop is part of the Power BI product suite. To monitor key data and share dashboards and reports, use the Power BI web service. To view and interact with your data on any mobile device, get the Power BI Mobile app on the AppStore, Google Play or the Microsoft Store. To embed stunning, fully interactive reports and visuals into your applications use Power BI Embedded.

Average Rating: 4.5/5.0

Total Reviews: 1,603

How Do G2 Users Rate Microsoft Power BI?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.4/10 (Category avg: 8.4/10)
  • Reports Interface: 8.9/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.6/10 (Category avg: 8.5/10)

Who Is the Company Behind Microsoft Power BI?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • Twitter: @microsoft
    13,091,739 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    232,750 employees on LinkedIn®
  • Ownership: MSFT

Who Uses This Product?

  • Who Uses This: Data Analyst, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 42% Large, 38% Medium

What Do G2 Reviewers Say About Microsoft Power BI?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Microsoft Power BI, allowing accessible data analysis for everyone.
  • Users find Power BI’s data visualization capabilities excellent for creating customized reports and dashboards quickly.
  • Users value the seamless integrations of Power BI, enabling efficient data connectivity and enhanced organizational analysis.
  • Users praise the powerful data analytics and visualization capabilities of Microsoft Power BI for insightful reporting.
  • Users love the powerful charting features in Power BI, enabling easy data visualization and report creation.
Cons
  • Users find the learning curve steep for Power BI, especially for beginners trying to connect data sources effectively.
  • Users find the slow performance of Power BI frustrating, especially when handling large datasets without optimization.
  • Users face performance issues with Power BI, especially regarding DAX queries and handling large data volumes, causing frustration.
  • Users often find data modeling complexities in Power BI challenging, leading to a steep learning curve and performance issues.
  • Users find the limited customization options in Power BI frustrating, constraining their ability to present data effectively.

What Are Recent G2 Reviews of Microsoft Power BI?

What Are G2 Users Discussing About Microsoft Power BI?

Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics, and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value.

Average Rating: 4.6/5.0

Total Reviews: 1,330

How Do G2 Users Rate Databricks?

  • Has the product been a good partner in doing business?: 8.9/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.3/10 (Category avg: 8.4/10)
  • Reports Interface: 9.1/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.6/10 (Category avg: 8.5/10)

Who Is the Company Behind Databricks?

  • Seller: Databricks Inc.
  • Company Website:
  • Year Founded: 2013
  • HQ Location: San Francisco, CA
  • Twitter: @databricks
    92,269 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    14,336 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 48% Large, 38% Medium

What Do G2 Reviewers Say About Databricks?

AI-generated summary from verified user reviews

Pros
  • Users enjoy the ease of use and extensive features of Databricks, streamlining data warehousing and machine learning tasks.
  • Users value the seamless integrations with AWS services that enhance efficiency and support diverse business needs.
  • Users appreciate the ease of use of Databricks, enhancing their experience with its intuitive interface and efficient features.
  • Users value the seamless collaboration provided by Databricks, enhancing teamwork on data projects and insights sharing.
  • Users value the effective data management features of Databricks, simplifying their workflows and enhancing decision-making.
Cons
  • Users face a steep learning curve with Databricks, as its complexity can be confusing for newcomers.
  • Users note that the cost of Databricks can be quite high, particularly for large data projects and limited free options.
  • Users express frustration over missing features in Databricks, limiting its effectiveness for complex deployments and custom setups.
  • Users find the steep learning curve of Databricks challenging, particularly for those unfamiliar with big data tools.
  • Users face unintuitive UI issues that lead to random errors and complicate the experience for non-technical users.

What Are Recent G2 Reviews of Databricks?

What Are G2 Users Discussing About Databricks?

Alteryx

Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial.

Average Rating: 4.6/5.0

Total Reviews: 863

How Do G2 Users Rate Alteryx?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.6/10 (Category avg: 8.4/10)
  • Reports Interface: 8.0/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Alteryx?

  • Seller: Alteryx
  • Company Website:
  • Year Founded: 1997
  • HQ Location: Irvine, CA
  • Twitter: @alteryx
    26,149 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2,312 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Analyst
  • Top Industries: Financial Services, Accounting
  • Company Size: 63% Large, 21% Medium

What Do G2 Reviewers Say About Alteryx?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use in Alteryx, finding it simple to automate tasks with drag and drop functionality.
  • Users value the automation capabilities of Alteryx, streamlining data processes and enhancing analytical efficiency.
  • Users find Alteryx to be very intuitive, making it easy for non-technical users to learn and utilize.
  • Users find that Alteryx's interface makes learning technology easy for everyone, even those without a tech background.
  • Users value Alteryx for its efficiency in managing data, streamlining workflows, and enhancing overall productivity.
Cons
  • Users highlight the expensive pricing of Alteryx, making it difficult for small teams or startups to afford licenses.
  • Users face a steep learning curve with Alteryx, requiring time to master its complex features.
  • Users find that Alteryx suffers from missing features, such as lack of direct database access and limited reporting tools.
  • Users find the learning difficulty of Alteryx steep, especially for those unfamiliar with RegEx and SQL.
  • Users experience slow performance with Alteryx, particularly when handling large workflows and during data wrangling tasks.

What Are Recent G2 Reviews of Alteryx?

Oracle Analytics Cloud

Oracle Analytics Cloud is a comprehensive cloud analytics platform that empowers you to fundamentally change how you analyze and act on information. Empower leaders, analysts, and IT to access data from wherever they are, even using mobile devices. Oracle Analytics Cloud helps organizations discover unique insights faster with machine learning. With augmented analytics, combine data from across your organization with third-party data and automate important and time-consuming tasks such as data preparation, visualization, forecasting, and reporting.

Average Rating: 4.1/5.0

Total Reviews: 293

How Do G2 Users Rate Oracle Analytics Cloud?

  • Has the product been a good partner in doing business?: 7.8/10 (Category avg: 9.2/10)
  • Steps to Answer: 7.9/10 (Category avg: 8.4/10)
  • Reports Interface: 8.4/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Oracle Analytics Cloud?

  • Seller: Oracle
  • Year Founded: 1977
  • HQ Location: Austin, TX
  • Twitter: @Oracle
    827,997 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    207,576 employees on LinkedIn®
  • Ownership: NYSE:ORCL

Who Uses This Product?

  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 61% Large, 28% Medium

What Do G2 Reviewers Say About Oracle Analytics Cloud?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the robust self-service analytics tools of Oracle Analytics Cloud, enabling seamless data exploration and collaboration.
  • Users appreciate the strong data visualization capabilities of Oracle Analytics Cloud, simplifying analysis for all organizational levels.
  • Users appreciate the intuitive and accessible interface of Oracle Analytics Cloud, enhancing data exploration across all technical levels.
  • Users appreciate the flexibility of Oracle Analytics Cloud, enabling fast analysis with minimal technical effort for all users.
  • Users praise the seamless integrations of Oracle Analytics Cloud, enhancing data management and collaboration across the organization.
Cons
  • Users often struggle with the high learning curve of Oracle Analytics Cloud, making initial adoption challenging for beginners.
  • Users find the complexity of Oracle Analytics Cloud daunting, especially during initial setup and configuration for new users.
  • Users find the complex usage of Oracle Analytics Cloud daunting, particularly during initial setup and advanced feature navigation.
  • Users find the limited customization options inadequate for highly specialized requirements in Oracle Analytics Cloud.
  • Users express concern over the infrequent software updates that lead to potential security vulnerabilities in Oracle Analytics Cloud.

What Are Recent G2 Reviews of Oracle Analytics Cloud?

What Are G2 Users Discussing About Oracle Analytics Cloud?

Kyvos Semantic Layer

Kyvos is a semantic layer for AI and BI. It gives organizations a single, consistent, business-friendly view of their entire data estate. By standardizing how data is defined and understood, Kyvos eliminates metric drift across BI tools and ensures that LLMs and AI agents work with governed business semantics rather than raw tables. Kyvos also delivers lightning-fast analytics at massive scale and high concurrency — including granular multidimensional analysis on the cloud — without the sluggish query times and escalating cloud costs that typically come with it. Why Organizations Use Kyvos Unified Semantic Foundation for AI and BI Kyvos semantic layer standardizes how metrics, KPIs, dimensions, hierarchies, relationships, calculations, and business rules are modelled across the enterprise — so that dashboards, analytics tools, notebooks, and AI systems all operate on the same understanding of the business. Kyvos enables: - Shared semantics — one common data language across every tool, team, and system - Governed access — data exploration within defined security, role, and permission boundaries - Platform interoperability — consistent semantic context across diverse platforms and environments - AI readiness — LLMs and agents work with governed business semantics rather than raw tables or ambiguous schema AI Grounded in Business Context Kyvos grounds AI systems in the governed semantic model, ensuring they operate on established business context rather than raw schemas — improving the accuracy, traceability, and reliability of AI-generated insights. Consistent Metrics Across BI Tools Kyvos centralizes metric and KPI definitions in the semantic layer and applies them consistently across every analytics interface — eliminating metric drift and improving trust in analytics. High-Performance Analytics at Scale Kyvos delivers high-performance analytics that scale with demand, enabling: - Sub-second query performance across massive datasets - High concurrency across thousands of users and workloads - Consistent response times regardless of data volume or concurrency - No performance degradation as adoption grows - Multidimensional Analytics on the Cloud Kyvos enables deep multidimensional analytics, supporting: - Granular analysis across billions of rows - Thousands of measures and dimensions in a single model - Fast drill-down across complex hierarchies - Full analytical depth without sacrificing query speed Cloud Cost Efficiency Kyvos serves analytics through its semantic layer rather than routing every query to the warehouse — reducing compute consumption across analytics and AI workloads. As adoption grows, organizations can scale users, workloads, and analytical complexity without a corresponding rise in warehouse compute costs.

Average Rating: 4.8/5.0

Total Reviews: 267

How Do G2 Users Rate Kyvos Semantic Layer?

  • Has the product been a good partner in doing business?: 9.6/10 (Category avg: 9.2/10)
  • Steps to Answer: 9.3/10 (Category avg: 8.4/10)
  • Reports Interface: 9.6/10 (Category avg: 8.8/10)
  • Calculated Fields: 9.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Kyvos Semantic Layer?

  • Seller: Kyvos Insights
  • Year Founded: 2014
  • HQ Location: Los Gatos, CA
  • Twitter: @KyvosInsights
    689 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    145 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Senior Software Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 57% Medium, 38% Large

What Do G2 Reviewers Say About Kyvos Semantic Layer?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Kyvos, allowing quick access to insights and simplifying complex data management.
  • Users appreciate the fast data processing of Kyvos, enabling instant analysis and visualization of large datasets.
  • Users value the remarkable speed and performance of Kyvos, enabling swift data analytics for large datasets.
  • Users appreciate the lightning-fast analytics of Kyvos Semantic Layer, making data processing and visualization seamless and efficient.
  • Users value the fast querying capabilities of Kyvos Semantic Layer, enabling quick analysis of large data volumes.
Cons
  • Users find the learning curve steep for Kyvos, especially with advanced features and MDX queries requiring specialized knowledge.
  • Users find the difficult setup of Kyvos Semantic Layer challenging, despite effective support easing the process.
  • Users find the initial setup and MDX complexity challenging, though support significantly eases the deployment process.
  • Users find feature limitations in Kyvos, particularly lacking advanced analytics and graphical options for data visualization.
  • Users note that there can be connectivity issues during integration, but support helps ease the process over time.

What Are Recent G2 Reviews of Kyvos Semantic Layer?

IBM Cognos Analytics

IBM Cognos Analytics is a business intelligence and analytics solution that uses agentic AI to help teams transform trusted data into actionable insights, build governed analytical applications, and make better decisions. Teams can explore data, monitor KPIs, analyze performance, forecast trends, and share insights across the business. The solution is built for business leaders, analysts, report authors, IT teams, and data governance teams that need governed reporting, self-service analytics, data modeling, and flexible deployment options. Common use cases include enterprise reporting, operational reporting, financial reporting, dashboarding, performance management, forecasting, and governed self-service analytics. It supports both centralized BI teams and distributed users who need consistent access to trusted analytics. Key capabilities: 1. Create governed reports and dashboards: Build, schedule, distribute, and manage reports, dashboards, and visualizations for teams, executives, and stakeholders. Support routine reporting, business reviews, and purpose-built analytical applications with consistent information. 2. Explore data with control: Use self-service analytics, certified data models, governed metrics, access controls, and auditability to keep reporting consistent across teams and departments. 3. Analyze and forecast faster: Use natural-language assistance, automated insights, and forecasting to help users understand data faster in supported versions and deployments. 4. Put Reporting Agents to work: Use agentic AI capabilities in supported versions and deployments to find reports, summarize results, share insights, and create or refine reports using natural language. 5. Deploy where the business needs it: Run Cognos Analytics in on-premises, IBM-hosted, hybrid, or certified container environments to align with infrastructure, security, and governance requirements. Cognos Analytics helps organizations reduce repetitive reporting work, improve consistency across metrics and dashboards, and make governed data analytics easier to access across the business.

Average Rating: 4.1/5.0

Total Reviews: 437

How Do G2 Users Rate IBM Cognos Analytics?

  • Has the product been a good partner in doing business?: 7.8/10 (Category avg: 9.2/10)
  • Steps to Answer: 7.6/10 (Category avg: 8.4/10)
  • Reports Interface: 8.0/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.1/10 (Category avg: 8.5/10)

Who Is the Company Behind IBM Cognos Analytics?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Analyst
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 58% Large, 26% Medium

What Do G2 Reviewers Say About IBM Cognos Analytics?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of IBM Cognos Analytics, facilitating quick data analysis and visualization.
  • Users appreciate the data visualization capabilities of IBM Cognos Analytics, enhancing understanding and insights effortlessly.
  • Users value the intuitive user interface of IBM Cognos Analytics, enhancing data comprehension and report creation efforts.
  • Users value the dashboard customization in Cognos Analytics, making complex data visuals clear and understandable.
  • 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 IBM Cognos Analytics complex to navigate and build reports, often requiring extensive training for effective use.
  • Users find the complex usage of IBM Cognos Analytics challenging, especially with report creation and software integration.
  • Users find the learning difficulty of IBM Cognos Analytics challenging, especially for novices trying to build reports.

What Are Recent G2 Reviews of IBM Cognos Analytics?

What Are G2 Users Discussing About IBM Cognos Analytics?

SAS Viya

SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control.

Average Rating: 4.3/5.0

Total Reviews: 775

How Do G2 Users Rate SAS Viya?

  • Has the product been a good partner in doing business?: 8.2/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.1/10 (Category avg: 8.4/10)
  • Reports Interface: 8.5/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.3/10 (Category avg: 8.5/10)

Who Is the Company Behind SAS Viya?

  • Seller: SAS Institute Inc.
  • Company Website:
  • Year Founded: 1976
  • HQ Location: Cary, NC
  • Twitter: @SASsoftware
    60,863 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    15,122 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Student, Biostatistician
  • Top Industries: Pharmaceuticals, Banking
  • Company Size: 33% Small, 33% Large

What Do G2 Reviewers Say About SAS Viya?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use in SAS Viya, enhancing data visualization and decision-making for businesses.
  • Users appreciate the advanced analytical capabilities of SAS Viya, making data analysis and decision-making more efficient.
  • Users value the sophisticated analytical capabilities of SAS Viya, enhancing decision-making and insights from diverse data sources.
  • Users value the end-to-end data lifecycle tooling in SAS Viya, enhancing insights and strategic decision-making capabilities.
  • Users value the powerful data visualization capabilities of SAS Viya, enhancing insights and decision-making in their organizations.
Cons
  • Users find SAS Viya difficult for non-technical users to navigate, impacting ease of access to reports and dashboards.
  • Users find the visualization complexity of SAS Viya challenging, especially for those without technical expertise.
  • Users find the learning curve challenging, especially for non-technical individuals navigating reports and dashboards.
  • Users find the difficult learning curve for SAS Viya challenging, especially for non-technical users attempting to access features.
  • Users find the expensive pricing of SAS Viya a potential barrier, complicating their decision-making process.

What Are Recent G2 Reviews of SAS Viya?

What Are G2 Users Discussing About SAS Viya?

Domo

Domo is the agentic platform for the intelligent enterprise, helping organizations connect, govern, activate, and distribute data and AI across their business. Built for enterprises, Domo works with existing cloud data platforms such as Snowflake, BigQuery, and Databricks to help teams turn governed data into AI-powered agents, apps, workflows, and analytics. Domo is built on three layers. The data foundation connects and governs data across cloud data platforms and business systems. The activation layer enables organizations to build AI agents, apps, workflows, automations, and dashboards on top of that foundation. The distribution layer delivers intelligence where work happens through embedded apps, mobile, dashboards, and AI assistants using Model Context Protocol (MCP). Governance underpins every layer, helping organizations scale AI and data products with security and trust. Key capabilities include: - Connecting and governing data across cloud data platforms and enterprise applications. - Building AI agents, apps, workflows, automations, dashboards, and analytics. - Delivering data and AI through dashboards, embedded apps, AI assistants, and AI agents. - Supporting both low-code and pro-code development for business and technical teams. - Applying governance, security, and access controls across data and AI. Organizations use Domo for AI agents, apps, and workflows, as well as business intelligence, operational analytics, embedded analytics, and executive reporting. By combining governed data, AI activation, app development, and distribution in a single platform, Domo helps organizations build and scale trusted data products across the enterprise.

Average Rating: 4.3/5.0

Total Reviews: 1,069

How Do G2 Users Rate Domo?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 9.2/10)
  • Steps to Answer: 7.9/10 (Category avg: 8.4/10)
  • Reports Interface: 8.5/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Domo?

  • Seller: Domo
  • Company Website:
  • Year Founded: 2010
  • HQ Location: American Fork, UT
  • Twitter: @Domotalk
    63,513 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,288 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Business Analyst
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 50% Medium, 28% Large

What Do G2 Reviewers Say About Domo?

AI-generated summary from verified user reviews

Pros
  • Users find Domo's ease of use and intuitive design invaluable for managing data efficiently and effectively.
  • Users value the flexible and user-friendly data visualization capabilities of Domo, enhancing their data analysis experience significantly.
  • Users find Domo's intuitive design empowering, facilitating easy access and effective data visualization for all skill levels.
  • Users praise Domo for its easy integrations, streamlining data management and enhancing real-time collaboration across various platforms.
  • Users value Domo's seamless integration capabilities, enabling efficient data management and real-time insights from various sources.
Cons
  • Users find the learning curve steep, often needing dedicated resources to manage updates and functionalities effectively.
  • Users report missing features in Domo, including flexibility in pivot charts and dynamic column options.
  • Users face significant data management issues with Domo, including unreliable connectors and challenging reporting functionality.
  • Users find Domo expensive, especially with drastic price increases that strain budgets and erode client trust.
  • Users find Domo's complexity hinders flexibility and speed in dataset management, making changes challenging and time-consuming.

What Are Recent G2 Reviews of Domo?

What Are G2 Users Discussing About Domo?

Dataiku

Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI. Governance is part of the build rather than something bolted on afterward, so teams ship faster while keeping performance, cost, and risk under control. The result: AI that moves from experimentation to trusted, measurable execution now, not in 18 months.

Average Rating: 4.4/5.0

Total Reviews: 218

How Do G2 Users Rate Dataiku?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 9.2/10)
  • Steps to Answer: 7.8/10 (Category avg: 8.4/10)
  • Reports Interface: 7.8/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Dataiku?

  • Seller: Dataiku
  • Company Website:
  • Year Founded: 2013
  • HQ Location: New York, NY
  • Twitter: @dataiku
    22,917 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,605 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Scientist, Data Analyst
  • Top Industries: Financial Services, Pharmaceuticals
  • Company Size: 59% Large, 23% Medium

What Do G2 Reviewers Say About Dataiku?

AI-generated summary from verified user reviews

Pros
  • Users find Dataiku easy to use, simplifying ML development and helping detect opportunities and risks effortlessly.
  • Users appreciate how Dataiku simplifies ML development, enabling quick training, evaluation, and understanding of data easily.
  • Users value the ease of use in Dataiku, enabling collaboration and simplifying complex data processes for all skill levels.
  • Users appreciate the easy integrations of Dataiku, facilitating collaboration across diverse analytics tools and skill sets.
  • Users commend the productivity improvement brought by Dataiku’s visual recipes and robust tools for analytics projects.
Cons
  • Users find the learning curve steep, making it challenging for beginners to fully utilize Dataiku's advanced features.
  • Users find the steep learning curve challenging, especially for beginners navigating Dataiku's advanced features.
  • Users face slow performance with Dataiku when managing large datasets, impacting efficiency and productivity.
  • Users find the difficult learning curve challenging for beginners, impacting their ability to maximize the platform's potential.
  • Users find the pricing high for small companies and students, impacting accessibility for basic projects.

What Are Recent G2 Reviews of Dataiku?

What Are G2 Users Discussing About Dataiku?

Amazon Quick

Amazon QuickSight is a cloud-based unified business intelligence (BI) service at hyperscale. With QuickSight, all users can meet varying analytic needs from the same source of truth through modern interactive dashboards, paginated reports, natural language queries and embedded analytics. With Amazon Q in QuickSight, business analysts and business users can use natural language to build, discover, and share meaningful insights in seconds, turning insights into impact faster. Over 100,000 customers use Amazon QuickSight. Learn more at https://quicksight.aws

Average Rating: 4.3/5.0

Total Reviews: 677

How Do G2 Users Rate Amazon Quick?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.0/10 (Category avg: 8.4/10)
  • Reports Interface: 8.2/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.0/10 (Category avg: 8.5/10)

Who Is the Company Behind Amazon Quick?

  • Seller: Amazon Web Services (AWS)
  • Year Founded: 2006
  • HQ Location: Seattle, WA
  • Twitter: @awscloud
    2,232,483 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    147,094 employees on LinkedIn®
  • Ownership: NASDAQ: AMZN

Who Uses This Product?

  • Who Uses This: Data Analyst, Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 40% Small, 36% Medium

What Do G2 Reviewers Say About Amazon Quick?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the s seamless integration of Amazon QuickSight with AWS services for effective dashboard creation.
  • Users value the ease of use of Amazon QuickSight, simplifying the creation of interactive dashboards effortlessly.
  • Users highlight the manual integration ease of Amazon QuickSight, streamlining data collection and workflow seamlessly with AWS.
  • Users value the fast and intuitive data visualization features of Amazon QuickSight, enhancing analytical capabilities effortlessly.
  • Users value the intuitive dashboard creation in Amazon QuickSight, enhancing data accessibility and team collaboration.
Cons
  • Users find limited customization in Amazon QuickSight, impacting advanced analytics and visual flexibility compared to competitors.
  • Users find the learning curve challenging, requiring prior knowledge for effective use of QuickSight's features.
  • Users note the limited visualization options in Amazon QuickSight, impacting flexibility and usability for data presentations.
  • Users note the missing features in QuickSight, especially in customization and advanced visual options compared to competitors.
  • Users find the poor interface design of Amazon QuickSight hinders usability and complicates access to advanced features.

What Are Recent G2 Reviews of Amazon Quick?

What Are G2 Users Discussing About Amazon Quick?

SAP Analytics Cloud

With the SAP Analytics Cloud solution, you can bring together analytics and planning with unique integration to SAP applications and smooth access to heterogenous data sources. As the analytics and planning solution within SAP Business Technology Platform, SAP Analytics Cloud supports trusted insights and integrated planning processes enterprise-wide to help you make decisions without doubt.

Average Rating: 4.2/5.0

Total Reviews: 749

How Do G2 Users Rate SAP Analytics Cloud?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.0/10 (Category avg: 8.4/10)
  • Reports Interface: 8.3/10 (Category avg: 8.8/10)
  • Calculated Fields: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind SAP Analytics Cloud?

  • Seller: SAP
  • Year Founded: 1972
  • HQ Location: Walldorf
  • Twitter: @SAP
    297,052 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    149,349 employees on LinkedIn®
  • Ownership: NYSE:SAP

Who Uses This Product?

  • Who Uses This: Senior Consultant, Consultant
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 49% Large, 28% Medium

What Do G2 Reviewers Say About SAP Analytics Cloud?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use in SAP Analytics Cloud, simplifying data understanding for everyday tasks and decision-making.
  • Users value the powerful data analysis capabilities of SAP Analytics Cloud for its seamless integration and advanced planning features.
  • Users value the strong visualization capabilities of SAP Analytics Cloud, enhancing data storytelling and stakeholder communication.
  • Users value the easy integrations of SAP Analytics Cloud, allowing seamless connectivity and enhanced collaboration across tools.
  • Users value the powerful integration and predictive modeling capabilities of SAP Analytics Cloud for efficient project management.
Cons
  • Users experience slow performance with large datasets, affecting efficiency and user satisfaction in SAP Analytics Cloud.
  • Users face a steep learning curve in SAP Analytics Cloud that can hinder effective usage without proper training.
  • Users face a steep learning curve with SAP Analytics Cloud, requiring training to navigate its advanced features effectively.
  • Users often face performance issues with SAP Analytics Cloud, particularly when handling large datasets and complex calculations.
  • Users note that handling large datasets can slow down performance, impacting their overall experience with SAP Analytics Cloud.

What Are Recent G2 Reviews of SAP Analytics Cloud?

What Are G2 Users Discussing About SAP Analytics Cloud?

Sigma

Sigma is the AI runtime layer for analytics, agents, and apps built on live warehouse data. It is a cloud analytics and business intelligence platform that helps business and technical teams explore live data, build reports and applications, and deploy AI agents directly on a cloud data warehouse, using a familiar spreadsheet interface alongside SQL, Python, and AI. - Analytics: Use Sigma for classic business intelligence workloads like pixel-perfect reporting, embedded analytics, and self-service access to data in an Excel-like interface. Build with AI, spreadsheet functions, SQL, or Python. - Agents: Deploy AI agents that act on live data and run multi-step workflows. Build them with natural language and your choice of enterprise LLM or warehouse AI. - Apps: Build AI Apps for operational work like planning and forecasting, scenario modeling, and approval routing, with writeback and governance automatically configured. Every artifact in Sigma inherits the security, permissions, and row-level access already set in the cloud data warehouse. Because governance is enforced at the source, anything a team builds is IT-approved from the start. Sigma solves a persistent tradeoff in enterprise data work. Business teams typically wait on a central data team to build reports and tools, while ad hoc AI and app-building tools produce work that sits outside IT's control. Sigma removes that tradeoff by keeping analysis, reporting, applications, and agents on live warehouse data under one set of permissions, so non-technical users build what they need while IT keeps a single, auditable system of control. Founded in 2014, Sigma is a privately held company headquartered in San Francisco, with offices in New York, London, and Sydney. More than 2,000 companies trust Sigma, including DoorDash, Blackstone, JPMorgan Chase, and Figma. Sigma is the business intelligence partner of the year for both Snowflake (2023-2026) and Databricks (2025-2026).

Average Rating: 4.4/5.0

Total Reviews: 544

How Do G2 Users Rate Sigma?

  • Has the product been a good partner in doing business?: 9.1/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.4/10 (Category avg: 8.4/10)
  • Reports Interface: 8.6/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.7/10 (Category avg: 8.5/10)

Who Is the Company Behind Sigma?

  • Seller: Sigma Computing
  • Company Website:
  • Year Founded: 2014
  • HQ Location: San Francisco, California
  • Twitter: @sigmacomputing
    1,556 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,417 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Customer Success Manager
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 58% Medium, 21% Large

What Do G2 Reviewers Say About Sigma?

AI-generated summary from verified user reviews

Pros
  • Users find Sigma's ease of use refreshing, allowing for quick learning and a straightforward setup process.
  • Users value the user-friendly interface of Sigma, facilitating easy metric management and dashboard creation.
  • Users find that Sigma greatly enhances data handling, streamlining processing and visualization for daily project tasks.
  • Users appreciate the responsive customer support of Sigma, ensuring quick resolution of issues and helpful follow-ups.
  • Users appreciate how Sigma provides clear, interactive visuals for simplifying complex datasets and tracking KPIs.
Cons
  • Users experience slow loading times with Sigma, causing inefficiencies and frustration during use.
  • Users experience slow performance with Sigma, particularly when handling complex tasks or large datasets, causing frustration.
  • Users find the limited customization of Sigma's charts and visualizations to be a drawback in their workflow.
  • Users experience a steep learning curve with Sigma, finding the dashboard building process unintuitive and challenging.
  • Users find Sigma lacks basic features like custom visualizations and flexible formatting, limiting advanced usage.

What Are Recent G2 Reviews of Sigma?

What Are G2 Users Discussing About Sigma?

Teradata Autonomous Knowledge Platform

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. Learn more at Teradata.com.

Average Rating: 4.3/5.0

Total Reviews: 354

How Do G2 Users Rate Teradata Autonomous Knowledge Platform?

  • Has the product been a good partner in doing business?: 8.2/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.1/10 (Category avg: 8.4/10)
  • Reports Interface: 7.7/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Teradata Autonomous Knowledge Platform?

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 69% Large, 22% Medium

What Do G2 Reviewers Say About Teradata Autonomous Knowledge Platform?

AI-generated summary from verified user reviews

Pros
  • Users highlight the extreme performance of Teradata Autonomous Knowledge Platform, emphasizing its speed in processing large data volumes.
  • Users value the high performance and scalability of Teradata for handling complex queries and data integration.
  • Users value the scalability of Teradata Autonomous Knowledge Platform, seamlessly integrating and managing vast data resources efficiently.
  • Users commend the extreme performance of Teradata, highlighting its speed in processing large datasets seamlessly.
  • Users value the fast processing of large datasets in Teradata, appreciating its stability and integration capabilities.
Cons
  • Users identify a steep learning curve for Teradata Autonomous Knowledge Platform, hindering new user adaptation and productivity.
  • Users find the steep learning curve of Teradata Autonomous Knowledge Platform challenging, especially for those less technically inclined.
  • Users find the complexity of the Teradata platform challenging, especially for non-technical users and new adopters.
  • Users struggle with the cost transparency of Teradata Autonomous Knowledge Platform, needing close management to avoid issues.
  • Users express concerns about the high cost of the Teradata Autonomous Knowledge Platform, highlighting affordability issues.

What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

Looker

Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation.

Average Rating: 4.4/5.0

Total Reviews: 1,590

How Do G2 Users Rate Looker?

  • Has the product been a good partner in doing business?: 8.9/10 (Category avg: 9.2/10)
  • Steps to Answer: 8.2/10 (Category avg: 8.4/10)
  • Reports Interface: 8.6/10 (Category avg: 8.8/10)
  • Calculated Fields: 8.4/10 (Category avg: 8.5/10)

Who Is the Company Behind Looker?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • Twitter: @google
    31,899,995 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG

Who Uses This Product?

  • Who Uses This: Data Analyst, Data Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 60% Medium, 20% Large

What Do G2 Reviewers Say About Looker?

AI-generated summary from verified user reviews

Pros
  • Users love the ease of use of Looker, making report creation simple for those with limited technical skills.
  • Users value the dynamic real-time reporting abilities of Looker, enhancing collaboration and decision-making across digital ad platforms.
  • Users love the easy integrations with various data sources, enhancing their analytics experience on Looker.
  • Users appreciate the seamless integrations with platforms like Salesforce, enhancing functionality and user experience in Looker.
  • Users appreciate the dynamic and real-time reporting capabilities of Looker, enhancing data sharing for digital ads.
Cons
  • Users find Looker's steep learning curve challenging, especially with LookML, making onboarding for beginners difficult.
  • Users find the steep learning curve of Looker challenging, especially for those lacking technical expertise.
  • Users experience slow loading times with Looker, particularly when handling larger datasets, complicating dashboard creation.
  • Users often experience slow performance with Looker, particularly during data loading and complex transformations.
  • Users find Looker to have high complexity, struggling with learning curves and limited visuals, affecting overall usability.

What Are Recent G2 Reviews of Looker?

What Are G2 Users Discussing About Looker?