Subscribe to the newsletter!

Gartners Magic Quadrant for BI Platforms 2024

My analysis of the Magic Quadrant for Analytics and BI platforms 2024!

Analytics and business intelligence (ABI) platforms enable less-technical users - including business people - to model, analyze, explore, share and manage data, and collaborate and share findings, enabled by IT and augmented by AI.

A quick view learns us that after a couple of years with only three leaders: PowerBI, Tableau and Qlik, we now have three vendors who break into the upper right quadrant this year: Google, ThoughtSpot and Oracle. No vendors were added or dropped, however Tibco is renamed as Spotfire in the 2024 quadrant.



Qlik stands as a Leader with its strong analytics and data integration capabilities, exemplified by Qlik Staige AI and Bedrock integration. It integrates seamlessly with Microsoft Fabric and Teams, providing an end-to-end data analytics solution. Despite its renewed market recognition, Qlik faces challenges with analytics market momentum, cloud or application ecosystem, and vertical solutions.

Salesforce (Tableau)

Salesforce's Tableau, a Leader, provides advanced augmented analytics through Tableau Pulse and a composable architecture. Renowned for corporate viability, Tableau's complexity within its product portfolio remains a challenge, despite its dedicated leadership within Salesforce.


Microsoft's Power BI is a standout Leader, integrated into the Fabric platform. Known for its competitive pricing, extensive functionality, and integration with MS365, Azure, and Dynamics, Microsoft leverages Gen AI (Copilot) and comprehensive integration options. Despite challenges with governance and interoperability with competitor platforms, Power BI's exclusive availability on Azure supports its robust ecosystem.


Google is a new Leader in the Gartner Magic Quadrant for BI and Analytics platforms, offering Looker with a multicloud architecture. Looker Studio (formerly Data Studio) is a flexible tool that can be used independently or connected to Looker for comprehensive data integration. Google's modular, headless BI capabilities integrate with its broader cloud ecosystem, including the LLM Gemini, though its visual data preparation tools are not as robust, making it less ideal for business users.


Oracle Analytics Cloud, a new Leader, integrates deeply with Oracle Fusion Apps and its enterprise cloud ecosystem. Oracle's significant investments in data management and integration highlight its strength in this quadrant, though its use cases outside the Oracle ecosystem are limited. Additionally, Oracle's offerings can be expensive for SMBs, and there is a lack of knowledgeable resources.


ThoughtSpot, another new Leader, offers Sage for Gen AI NLQ and SpotIQ for automated insights. With a modular approach supporting a modern data stack, ThoughtSpot excels in providing a composable, analytics-as-code environment, though it lacks a comprehensive cloud or application ecosystem and advanced data science integration.



Alibaba is a Challenger with its Quick BI platform, primarily serving the APAC region. The Smart Q LLM integrates AI features, although this area is not a major focus for Alibaba.


AWS, classified as a Challenger, offers QuickSight, integrating Amazon Q LLM and focusing on CSP Cloud integration. Known for serverless scalability and performance, AWS is entirely cloud-based but requires extra paid services for additional functionalities and lacks a native ETL solution, relying on Glue as a pay-for-use service.


Domo, also a Challenger, targets marketing analytics and the SMB market. It supports the use of external AI models from providers like Hugging Face and OpenAI. However, Domo operates outside a larger cloud or application ecosystem and lags in natural language querying (NQL).


MicroStrategy is a Challenger offering MicroStrategy AI, which includes Gen AI features like Auto SQL and Auto Dashboards. It is known for open interoperability and strong enterprise reporting but suffers from low market awareness.



IBM, a Visionary, provides Cognos with a strong focus on enterprise reporting and an analytics catalog vision. However, its cloud offerings are limited to IBM Cloud, which lags behind competitors.

Pyramid Analytics

Pyramid Analytics, a Visionary, offers ML-based data preparation, wrangling, and discovery in a low-code/no-code environment. It is cloud-agnostic and supports multiple LLMs, Jupyter notebooks, and AutoML. However, it lacks a metrics layer and broader market awareness.


SAP Analytics Cloud positions SAP as a Visionary, extending planning and analytics capabilities through RISE. It integrates SAP Datasphere for a unified business data fabric but has average product capabilities and limited adoption outside its ecosystem.


SAS, another Visionary, includes SAS Visual Analytics within its end-to-end SAS Viya portfolio. It promotes an AI Core approach and collaboration within a unified platform, offering a low-code/no-code UX. Despite its open architecture, SAS has limited interoperability and is not a native cloud solution.


Spotfire, formerly TIBCO Spotfire and now a Visionary, combines visual analytics, data science, and data-wrangling. It is cloud-agnostic or on-premise and targets industry-specific use cases. However, it faces high costs and a steep learning curve.


Tellius, a Visionary, emphasizes strong NQL and ML algorithms with an industry focus. Leveraging Apache Spark for performance, it struggles with reduced market momentum and product gaps in reporting and data storytelling.

Niche Players


GoodData, a Niche Player, emphasizes an "Analytics as code" approach with a metrics store and semantic layer. It is cloud-native and SaaS-based but caters primarily to mature buyers.


Incorta, another Niche Player, specializes in DWH automation for applications like SAP and Oracle. It appeals to low-maturity customers but lacks NQL and depends on integration with other analytics and BI tools.


Sisense, a Niche Player, offers Fusion APaaS with a composable, code-first approach. It includes LLM and AI experiences but has limited ecosystem support and low community engagement.


ZoHo Analytics, also a Niche Player, integrates Gen AI through OpenAI and targets SMBs with line-of-business analytics. It integrates well with ZoHo business applications but sees limited adoption in advanced analytics, as ABI is not its primary focus.

Honorable Mentions

Some are tools that are adjacent to the ABI market, others are full ABI platforms but didn't make the top 20:


Uses AI to automate data engineering, data analytics, and data science tasks.


An augmented analytics platform for data exploration, analysis, and insights discovery. It helps monitor key metrics, identify performance drivers, and detect critical issues quickly.


A semantic layer platform.


An intelligent planning platform that combines analytics with financial planning and analysis (FP&A).


Provides a consistent and governed metrics layer.

FanRuan Software

A Chinese ABI platform that is report-centric.


Uses AI to automate the analysis and presentation of data, making it easier to consume.


Focuses on data storytelling with augmented and natural language query (NLQ) capabilities to automate the creation of data stories.


Important features to look for this year include Natural Language Querying (NQL) and integration with Large Language Models to literally talk to your data or to enhance the user experience of executing the analysis.

Another key criterion is how well the ABI integrates into an ecosystem. Google, AWS, and Microsoft benefit from being part of comprehensive cloud ecosystems (GCP, AWS, and Azure). But beware, these are not included in the pricing of the ABI as such.

Salesforce (Tableau), SAP, Oracle, and ZoHo gain advantages from their integration with business applications like ERP and CRM, but sometimes these ABI's have limited usecases outside this closed ecosystem.

In contrast, ABIs like Qlik and ThoughtSpot lack these ecosystem benefits but still get in the leaders quadrant without the merits of being part of an ecosystem. This speaks to their completeness of vision and ability to execute without having to rely on the ecosystem to drive sales and adoption.

In conclusion, selecting the right ABI platform is crucial for leveraging data effectively within your organization.

If you are in the process of selecting an analytics and BI platform and need some guidance, don't hesitate to contact me to discuss tool selection!