Dataiku at the Gartner Data & Analytics Summit

Not only is Everyday AI a change in the way we think about AI; it is also a change in the way companies need to be structured, run, communicated with, and incentivized. Many companies are looking at deploying similar strategies to benefit from the shift in the way AI is being developed and implemented.

Hear from a Fortune 500 pharmaceutical company to learn:

• How they enabled their organization to achieve Everyday AI

• How this new approach makes data and AI accessible to different teams, technical and non-technical, to make data-driven decisions

• The keys to success for implementing this new strategy across multiple organizations

Dataiku is the world’s leading platform for Everyday AI, systemizing the use of data for exceptional business results. Organizations that use Dataiku elevate their people (whether technical and working in code or on the business side and low- or no-code) to extraordinary, arming them with the ability to make better day-to-day decisions with data. More than 450 companies worldwide use Dataiku to systemize their use of data and AI, driving diverse use cases from fraud detection to customer churn prevention, predictive maintenance to supply chain optimization, and everything in between.

Dataiku, a 2x Leader (2020 and 2021) in the Magic Quadrant™ for Data Science and ML Platforms, is cited by Gartner in both the Market Guide for Multipersona Data Science and ML Platforms and the Market Guide for DSML Engineering Platforms.

Per Gartner, “The AI & data science platform market is due to grow to over $10 billion by 2025 at a 21.6% compounded annual growth rate. This growth mirrors the investments made by organizations in DSML initiatives, which are largely turning from strategy to execution.” Analytics leaders and practitioners alike can use this research for insights on the two types of platforms, functionalities that each prioritize, key trends in each market, and more.

Gartner, Inc., Market Guide for DSML Engineering Platforms, Afraz Jaffri, Erick Brethenoux, et al. May 2022. Market Guide for Multipersona Data Science and Machine Learning Platforms, Pieter den Hamer, Carlie Idoine, et al. May 2022. 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. © [2022] Gartner, Inc. and/or its affiliates. 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 and MAGIC QUADRANT are registered 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. 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 & Advisory 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, Magic Quadrant for Data Science and Machine-Learning Platforms, Peter Krensky, Carlie Idoine, Erick Brethenoux, Pieter den Hamer, Farhan Choudhary, Afraz Jaffri, Shubhangi Vashisth, 1 March 2021