While we’re proud to be a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms for the fourth time, the recognition doesn’t stop there. Dataiku is also recognized in the 2025 Gartner Critical Capabilities for Data Science and Machine Learning Platforms, Core Data Science report, ranking #1 for the Product Owner Use Case.
This year’s Critical Capabilities report reflects continued evolution of the data science and ML space. With updated evaluation criteria, including dedicated Use Cases for Product Owners, Data Analysts, Data Scientists, and Model Validators, this report offers a clear lens for understanding how well vendors align with specific enterprise roles and responsibilities.
And when it comes to enabling product owners to steer AI strategy with impact and governance? Dataiku leads the pack.
What's New in This Year's Evaluation?
Unlike previous editions, the 2025 report places a sharper focus on role-based value delivery. Gartner defines the Product Owner Use Case as the “use of the DSML platform to prioritize and oversee the development process to align with business goals and user needs.” In other words, it’s a test of how well a platform empowers those responsible for managing data initiatives, aligning teams, and delivering business outcomes — not just building models.
Key evaluation criteria for this use case included:
- Project and Value Management (30%): The capability to scope, define and measure projects by defining business outcomes and success criteria.
- Governance and Risk Management (20%): The capability to create, enforce and measure compliance against governance controls and reduce risk.
We believe Dataiku’s #1 placement here reflects our strong foundation in both of these areas. As The Universal AI Platform™, we empower product owners to orchestrate complex initiatives across the data lifecycle while also delivering transparency, auditability, and control.
Why We Believe Dataiku Received This Ranking
Here’s why we believe Dataiku ranked highest for this critical role:
✅ Governance and Oversight From the Ground Up
From role-based access controls to automated documentation and lineage tracking, Dataiku provides a governance-first foundation that enables confidence at scale. Built-in features like governance dashboards, approval workflows, and project-level auditability ensure product owners always have a pulse on project health and risk exposure.
✅ Transparent, Traceable, and Trustworthy AI
Product owners don’t just need results — they need to know how those results were achieved. Dataiku’s commitment to explainability, bias detection, and model risk management enables organizations to meet internal and external requirements for trust and transparency.
✅ Alignment With Business Value
With Dataiku, project managers can define success criteria, assign business goals to projects, and continuously monitor value delivery, all in one platform. Whether you’re tracking model adoption or quantifying impact through integrated metrics, Dataiku connects technical progress with business ROI.
✅ Collaboration Without Chaos
Dataiku’s visual tools and no-code features enable product owners to stay engaged throughout the lifecycle — no Python required. At the same time, coders and engineers can go deep with code and integrate with Git, CI/CD, and MLOps tools. This flexibility helps teams stay aligned without compromising on depth or speed.
Recognized Across the Board
Check out the scores Dataiku received across all Use Cases:
- 3.68/5 in the Product Owner Use Case (Dataiku ranked first out of 16 vendors)
- 3.62/5 in the Model Validator Use Case (Dataiku ranked top three out of 16 vendors)
- 3.76/5 in the Data Analyst Use Case (Dataiku ranked top three out of 16 vendors)
- 3.51/5 in the Data Scientist Use Case (Dataiku ranked top five out of 16 vendors)
We believe this recognition reinforces the breadth and depth of Dataiku across all types of users in the enterprise, both as individuals and together.
Build Trustworthy AI, Together
As roles like product owners, analysts, and model validators take center stage in shaping enterprise AI, platforms must meet each of them where they are — and help them work together to deliver impact, responsibly and at scale.
That’s exactly what the Gartner Critical Capabilities report is designed to help you do:
✔️ Identify the right capabilities for your team’s needs
✔️ Understand how platforms compare in real-world use
✔️ Make confident, future-ready technology decisions
Whether you’re refining your AI strategy, evaluating tools, or simply looking for a clearer path forward — this report is a must-read. And if you'd like to go further, we're here to talk through your specific goals, use cases, and questions.
Gartner, Critical Capabilities for Data Science and Machine Learning Platforms, Core Data Science, Afraz Jaffri,Tong Zhang, Deepak Seth, Maryam Hassanlou, Yogesh Bhatt, 4 June 2025. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. GARTNER is a registered trademark and service mark, and MAGIC QUADRANT and PEER INSIGHTS are trademarks and service marks, of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Dataiku. Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences with the vendors listed on the platform, should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates.