DATAIKU

Ranked #1 in 3 Core Data Science
Use Cases

The Gartner Critical Capabilities for Data Science & ML Platforms,
Core Data Science

See why Dataiku is placed highest (out of 18 vendors evaluated) for all three use cases — expert data science teams, line of business teams, and fusion teams, with the highest score for the latter — in this report, the essential companion piece to the Gartner® Magic Quadrant™ for DSML Platforms.

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Dataiku: A 3x Leader and The Universal AI Platform

Dataiku has been named a Leader in the 2024 Gartner Magic Quadrant for DSML Platforms. Among all evaluated vendors, Dataiku is placed furthest on the “Completeness of Vision” axis. Dataiku was also named a Leader in 2021 and 2020, before the Generative AI boom.

Dataiku, the Universal AI Platform, drives usability by everyone, from the code-free to the code-first, bringing analytics and AI intelligence across the enterprise.

Dataiku is beloved by data leaders and users alike. We’re the only platform on the market that unifies all your data work, from analytics to Generative AI, and all your people, from data scientist to data consumers and more.

But don’t just take our word for it — see what hundreds of people are saying about Dataiku behind our back.

Succeed in the Era of Generative AI

Unite Your Teams, Operations, & Tech With Dataiku

Easily Collaborate on Data & AI Projects

Dataiku empowers tech experts (so they can spend more time on high-impact AI projects), business experts (to untap new opportunities with the power of AI), and enterprise leaders (to drive business decisions for maximum impact).

Whether you’re a code-first data scientist or a low-code analyst, Dataiku makes collaborative development between groups easy.

Reduce Operational Risk

Underpin all processes with the governance required to leverage AI at scale and make informed decisions about risks and resources.

With a central control tower known as Dataiku Govern, teams can ensure centralized program oversight, more critical now than ever in the era of Generative AI.

Build Better & Faster

Customers routinely cite a 60%-80% reduction in time spent to go from data and AI project ideation to production.

From data access and preparation through modeling, app development, production deployment, and maintenance, whether traditional machine learning, Generative AI, or a combination of both, Dataiku helps teams accelerate their work so that they can take on more projects.

“Dataiku: Enabling High Velocity Data Science”

— Data Scientist in the insurance industry (Jan. 23, 2024) (Source)

“Polished and comprehensive end-to-end data science platform for all personas.”

— Product Owner in the retail industry (Dec. 19, 2023) (Source)

“Dataiku empowers all users to contribute in meaningful ways and innovate.”

— Strategy Associate in the finance industry (Jan 21, 2024) (Source)

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Gartner, Critical Capabilities for Data Science and Machine Learning Platforms, Core Data Science, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Raghvender Bhati, Maryam Hassanlou, Tong Zhang, 24 June 2024. 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, not do they represent the views of Gartner or its affiliates.