Dataiku: A Gartner Magic Quadrant Leader in Data Science and Machine-Learning Platforms

Dataiku Company, Dataiku Product Lynn Heidmann

Our 2019 ended with a bang with the announcement that Dataiku became a unicorn valued at $1.4 billion and gained a new investor (CapitalG). On top of all of that excitement, we’re thrilled to kick off the year by being named a Leader in the Gartner 2020 Magic Quadrant for Data Science and Machine-Learning Platforms!

Heads Up!

Check out this blog post about the Gartner 2021 Magic Quadrant for Data Science and Machine-Learning platforms for the most recent update.


Grab a complimentary copy of the Gartner 2020 Magic Quadrant for Data Science and Machine-Learning Platforms.


So what does this news mean for us practically? Not much, actually. Our plan for 2020 and beyond is - and always has been - to stay laser focused on helping organizations worldwide on their path to Enterprise AI via:


We will continue to provide tools that enable everyone (whatever their technological skills) to leverage elastic resources. For example, with Dataiku 6, we delivered fully managed Kubernetes cluster capabilities. In addition, Dataiku will keep integrating the most recent technologies in its stack in order to lower the barrier of integration for companies themselves and allow for organizations to move quickly along with the fast-paced AI world. These include computation, storage, programming languages, machine learning technologies, and more.

Responsible AI

We firmly believe that as a technology vendor, making it easy for customers to implement responsible AI - i.e., AI that is not only ethical, but sustainable and interpretable as well - is an obligation. We made strides toward this goal in 2019 with additional white-box AI features in Dataiku 6, and we plan to release even more in 2020.

Our Unique, End-to-End, Collaborative Approach

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 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.

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