Gartner Research

Four Data Management Best Practices for AI

Published: 18 August 2017

ID: G00328322

Analyst(s): Svetlana Sicular , Roxane Edjlali


Having the right data is a prerequisite to AI. To succeed in delivering on AI business value, data and analytics leaders need to expand and adjust their data management strategy and data governance to master the art of AI.

Table Of Contents
  • Key Challenges



  • Invest for the Long Term in Data for AI
  • Develop Data Understanding as Key to AI Success
  • Evaluate the Data Fit for AI
  • Include Data Management Requirements When Deploying Models

Gartner Recommended Reading

©2021 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates. This publication may not be reproduced or distributed in any form without Gartner’s prior written permission. It consists of the opinions of Gartner’s research organization, which should not be construed as statements of fact. While the information contained in this publication has been obtained from sources believed to be reliable, Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartner research may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such. Your access and use of this publication are governed by Gartner’s Usage Policy. Gartner prides itself on its reputation for independence and objectivity. Its research is produced independently by its research organization without input or influence from any third party. For further information, see Guiding Principles on Independence and Objectivity.

Already have a Gartner Account?

Purchase this Document

To purchase this document, you will need to register or sign in above

Become a client

Learn how to access this content as a Gartner client.