Gartner Research

Machine-Learning and Data Science Solutions: Build, Buy or Outsource?

Published: 30 November 2016

ID: G00315415

Analyst(s): Peter Krensky , Alexander Linden

Summary

Any new machine-learning or data science project presents the decision to build, buy or outsource a solution. A series of key questions and selection criteria guide data and analytics leaders to the optimal approach as they pursue their business intelligence and analytics modernization strategy.

Table Of Contents

Analysis

  • Introduction
  • 1. Is There a Packaged Application Available That Exactly Solves the Analytical Problem at Hand?
  • 2. Is There a Packaged Application Available That Meets Many of — Though Not All — Your Requirements?
  • 3. Is There a Packaged Application Available That Meets All Criteria, but Is Difficult to Implement Because Your Technology Stack Is Too Exotic or Idiosyncratic?
  • 4. Is Analytics a Critical Differentiator for Your Business?
  • 5. Is Your Analytics Scenario Unique?
  • 6. Is Your Industry One in Which New Kinds of Data Have Become Available, or a New Business Process Has Become Amenable to Data Science?
  • 7. Does Your Domain Require You to be Agile?
  • 8. Do You Have Access to Data Science Talent?

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