Big Data Analytics Failures and How to Prevent Them

Archived Published: 07 August 2015 ID: G00272497


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"Fail fast" is the mantra of the big data community, but information about actual failures is scarce. This research illustrates the causes of failures using real-life examples. It discusses lessons learned and measures to prevent mistakes by technical professionals involved in big data initiatives.

Table of Contents

  • Problem Statement
  • The Gartner Approach
  • The Guidance Framework
    • Strategy
    • Skills
    • Analytics
    • Part 1 โ€” Prevent Big Data Strategy Failures
      • Focus On Delivering Business Value
      • Select the Right Use Cases
      • Overcome Organizational Inertia
    • Part 2 โ€” Prevent Big Data Skills Shortcomings
      • Build a Multidisciplinary Team
      • Address Adjacent Technologies
    • Part 3 โ€” Prevent Big Data Analysis Pitfalls
      • Ask the Right Questions
      • Question Your Data
      • Apply the Right Models
  • Gartner Recommended Reading
© 2015 Gartner, Inc. and/or its Affiliates. All Rights Reserved. Reproduction and distribution of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartners research may discuss legal issues related to the information technology business, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice.

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