Gartner Research

Major Myths About Big Data's Impact on Analytics

Published: 15 September 2014

ID: G00269250

Analyst(s): Gareth Herschel , Carol Rozwell, Lisa Kart, Mark Beyer , Alexander Linden , Kimberly Harris-Ferrante , Noha Tohamy , W. Roy Schulte


The huge and excited debate about big data has led to the creation of many myths. We dispel some of them here so that business analytics leaders can devise sound strategies — or enhance existing ones — for analyzing big data.

Table Of Contents


  • Myth No. 1: 80% of All Data Is Unstructured
  • Myth No. 2: Advanced Analytics Is Just an Advanced Version of "Normal" Analytics
  • Myth No. 3: All You Need Is Embedded Analytics
  • Myth No. 4: Improved Tools Will Replace Data Scientists
  • Myth No. 5: Great Data Scientists Must Have a Ph.D. in Statistics or Operations Research
  • Myth No. 6: Descriptive Analytics Looks to the Past but Predictive Analytics Looks to the Future
  • Myth No. 7: Fast Analytics Equals Real-Time Analytics
  • Myth No. 8: We Can Predict Almost Anything With Big Data
  • Myth No. 9: Big Data Isn't Biased

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