DataRobot included for the first time as a ‘Visionary’ in the 2019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

The 2019 edition of Gartner's famous Magic Quadrant for Data Science and Machine Learning Platforms came out this week and DataRobot was positioned in the ‘Visionaries’ quadrant. We also achieved one of the furthest overall positions for completeness of vision, alongside two other vendors. For those of you who follow the MQ, we feel this is an impressive first showing and underscores the disruptive impact we’re having on the market. After all, we were the company that created the automated machine learning category. Last year, we chose not to participate in the MQ, but Gartner's influence on the market is undeniable.

It appears that our thinking aligns well with Gartner's, particularly around augmented analytics. In their Top 10 Strategic Technology Trends for 2019, Gartner states that “By 2020, more than 40% of data science tasks will be automated.” And, “Through 2020, the number of citizen data scientists will grow five times faster than expert data scientists.”

We have invested arguably more than any other vendor in the development of an augmented analytics platform that our customers are using to transform how they operate. With DataRobot’s unprecedented degree of automation, data science skills are democratized throughout an organization – allowing data scientists to be more productive and enabling business users to function as citizen data scientists and inject AI and machine learning into every key business decision.

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This is why we’re excited to be included for the first time as a ‘Visionary’ on the 2019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. This Magic Quadrant includes insight collected from thousands of data scientists, citizen data scientists, and other data and analytics professionals, including several highly-satisfied DataRobot customers.

We’re proud to be the driver behind the latest wave of analytics disruption because we help organizations utilize the teams they already have in place to embrace data science and machine learning, and become an AI-driven enterprise. Other key points mentioned by Gartner include customer feedback about our strong customer experience and our market responsiveness.

Compared to stalwarts IBM, SAS and others, DataRobot is relatively new to the market, but we launched the world’s first automated machine learning platform in 2013. Today we deliver the most mature and full-featured product in the augmented segment that will dominate spending in 2019 and beyond. In 2018 we added significant time series and model management capabilities to the platform, as well as other capabilities to serve the end-to-end data science needs of our customers. And we’re just getting started...

We know that choosing the right data science platform is critical, and we want you to understand all of your options so you can make an informed choice. That’s why we’re pleased to offer you a complimentary copy of this valuable research by Gartner. In it, we are confident you’ll learn more about Gartner’s view on augmented data science, and see why DataRobot is positioned as a 'Visionary' in our first year on this important Magic Quadrant.

 

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Gartner Magic Quadrant for Data Science and Machine Learning Platforms, 28 January 2019, Carlie Idoine, Peter Krensky, Erick Brethenoux, Alexander Linden. 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 https://www.datarobot.com/gartnerMQ.

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, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.


 

About the Author: 

Tim Young is responsible for global marketing at DataRobot. He has over 25 years of experience marketing high-tech enterprise products in the data management, analytics, and SaaS spaces. He has run marketing operations for global companies including IBM, Oracle, Netezza, and Workday. Tim brings a practical global perspective to DataRobot having managed marketing teams in Australia, Asia, U.K., Europe, and the U.S.