Gartner Research

Four Steps to Effective Crowdsourcing of Data Science Projects

Published: 16 June 2014

ID: G00259860

Analyst(s): Douglas Laney , Alexander Linden


A few companies are starting to use crowdsourcing to solve tough problems in data science, saving both time and money, but challenges exist. We describe four steps business analytics leaders should take to avoid the main pitfalls.

Table Of Contents
  • Key Challenges



  • Ask a Data Scientist to Describe the Problem for Crowdsourcing
  • Choose Projects Carefully — Crowdsourcing Isn't a Panacea
  • Consider the Legal Implications of Crowdsourcing
  • Use Data Obfuscation to Preserve Your Confidentiality

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