Industry Analyst Recognition for Dataiku

The 2020 Magic Quadrant for Data Science and Machine-Learning Platforms

Dataiku Identified as a LEADER

This is the third consecutive year that Dataiku has been recognized in this report.

We take pride in creating Dataiku as the only data science, machine learning, and AI platform on the market that provides an optimized experience for everyone – from business to analyst to data scientists. That means full coding environments and flexibility for coders as well as visual tools and guidance for data novices. And it’s also the only platform that covers every step of the data pipeline (from connecting to data all the way through operationalization and monitoring) all in one place with one, single UI for a unified Enterprise AI strategy.

Gartner Peer Insights

“Dataiku is probably the only true end to end platform in the market. And an incredible bridge between multiple choices of computation and storage for Data Science. Path to production becomes support straight forward with the API deployer and the bundling from DSS studio towards automate is a very straight forward way to deploy data science use-cases across an enterprise.”

– VP of Data Science, Services Industry

The 2020 Multimodal PAML Wave

Dataiku Named a LEADER

“Dataiku ascends to the crème de la crème. It’s hard to believe that Dataiku is only seven years old. In that short time, the vendor has been on an unstoppable march toward democratizing its enterprise PAML for a host of different roles within an enterprise, from business analysts to data scientists. It also offers persona-targeted training and enablement programs that help enterprises enable a large number of users with data science capabilities.”

Omdia Decision Matrix: Selecting an Enterprise ML Development Platform, 2020–21

Dataiku Named a LEADER

“Dataiku DSS is designed for enterprises, supporting multiple teams with 1000s of users able to access the same platform. The platform is also designed for multiple roles: technical coders and non-coders, data scientists and business domain analysts. The platform’s self-service analytics helps break silo department walls and provides a single point for accessing data, integrating with legacy data sources across hybrid infrastructure, and reducing time wasted accessing data.”

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is 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 Magic Quadrant for Data Science and Machine Learning Platforms, Peter Krensky, Pieter den Hamer, Erick Brethenoux, Jim Hare, Carlie Idoine, Alexander Linden, Svetlana Sicular, Farhan Choudhary, 11 February 2020. 

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 or other designation. 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 Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences and do not represent the views of Gartner or its affiliates. The GARTNER PEER INSIGHTS Logo is a trademark and service mark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved. Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences and do not represent the views of Gartner or its affiliates.

OMDIA is a registered trademark of Informa PLC and/or its affiliates. The information herein published by Omdia as part of a comprehensive research deliverable and should be evaluated in the original context. Source – Omdia Decision Matrix: Selecting an ML Development Platform, 2020–21. Results are not an endorsement of Dataiku. Any reliance on these results is at the third party’s own risk. Licensed reprints the entire research solution may be available via [email protected]