For the second year in a row, Domino is named a Visionary in Gartner’s Magic Quadrant for Data Science and Machine-Learning Platforms.

We are pleased to offer a complimentary copy of this important research into the data science platforms market.

Download the report to learn:

  • How Gartner defines the Data Science Platform category, and their perspective on the evolution of the data science platform market in 2018.
  • Which data science platform is right for your organization.
  • Why Domino was named a Visionary in 2018.

About Domino Data Lab

Domino Data Lab provides the world’s most advanced data science solution, powering organizations that are using predictive models to drive their business. Companies including Allstate, Coatue, Dell, Bayer, Moody’s, Tesla, and startups alike use Domino to accelerate breakthrough research, increase collaboration and productivity of data scientists, and more rapidly deliver models to drive business impact.

About Gartner

Gartner, Inc. is the world’s leading research and advisory company. They help business leaders across all major functions in every industry and enterprise size with the objective insights they need to make the right decisions. They have been publishing the Magic Quadrant for Data Science Platforms (titled Magic Quadrant for Advanced Analytics Platforms prior to 2017) since 2014.

Gartner: Magic Quadrant for Data Science and Machine-Learning Platforms, Alexander Linden, Peter Krensky, Jim Hare, Carlie J. Idoine, Svetlana Sicular, Shubhangi Vashisth, February 2018. 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 of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved.

We are sorry, but this report is no longer available.

To learn more about the data science platform market, the following is an excerpt from our CEO, Nick Elprin. If interested in more information on the data science platform market the full blog post, The Forrester Wave™: Notebook-Based Predictive Analytics And Machine Learning Solutions, Q3 2018, and WSJ article "Why Models Will Run the World" are available.

Excerpt from Nick Elprin's "Reflections on the Data Science Platform Market"

"Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. There are dozens of products describing themselves using similar language despite addressing different problems for different types of users. Not only has this confused data scientists, it’s also affected us as a software vendor: some analyses of the market lump Domino together with products completely different from ours, forcing us to answer questions about how we compare to products that address fundamentally different needs and use cases. It has felt, at times, like being an automaker and watching others compare our cars to submarines, airplanes, and scooters.

We’ve been pleasantly surprised to see, over the past six months especially, an emerging clarity in how companies are thinking about these products when equipping their data science teams with best-of-breed technologies. As often happens, this clarity is emerging simultaneously from different corners of the world, reflecting what seems to be the zeitgeist of the data science platform market.

The three segments that have crystallized are:

  1. Automation tools
  2. Proprietary (often GUI-driven) data science platforms
  3. Code-first data science platforms

Latest resources