30 Can’t miss Harvard Business Review articles on Data Science, Big Data and Analytics

Here are 30 Harvard Business Review (HBR) articles on big data, data science and analytics that provide insights about the latest technology and happenings in the world of data.

There are dozens of HBR articles that are worth recommending, but here are our picks on big data, data science and analytics collected using most popular and next recommended article filters based on search term.

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On Data Science

  1. Data Scientist: the sexiest job of the 21st century by Thomas H. Davenport and D.J. Patil (Oct 2012)
    How the idea of LinkedIn's People You May Know feature really clicked! The key player involved was a "Data Scientist", a title coined by the two authors.
  2. The Sexiest Job of the 21st Century is Tedious, and that Needs to Change by Sean Kandel (Apr 2014)
    Which phase does a data scientist spend more time on? Data Discovery, data structuring and creating context. Should they shift their focus?
  3. What Every Manager Should Know About Machine Learning by Mike Yeomans (July 2015)
    With the right mix of technical skill & human judgment, machine learning could be a new tool for decision makers. Learn what mistakes to avoid.
  4. Data Scientists Don’t Scale by Stuart Frankel (May 2015)
    We are at a new phase of big data. Is Data capture and storage now less relevant than making it more useful & impactful?
  5. Get the Right Data Scientists Asking the “Wrong” Questions by Josh Sullivan (Mar 2014)
    What makes an exceptional data scientist? Data by itself is meaningless. The skill & curiosity is what makes the difference.
  6. A Data Scientist’s Real Job: Storytelling by Jeff Bladt and Bob Filbin (Mar 2013)
    How to derive insights & intuitions from data? We “humanize” the data by turning raw numbers into a story about our performance.
  7. What Separates a Good Data Scientist from a Great One by Thomas C. Redman (Jan 2013)
    Better than the Best! Great data scientists bring four mutually reinforcing traits to bear that even the good ones can’t.
  8. Still the Sexiest Profession Alive by DJ Patil (Nov 2013)
    Data scientist jobs are very much in demand as companies grapple with the challenge of making valuable discoveries from Big Data. Is a huge crowd just joining the bandwagon?
  9. 10 Kinds of Stories to Tell with Data by Tom Davenport (Nov 2013)
    Narrative is—along with visual analytics—an important way to communicate analytical results to non-analytical people. Explore the 10 types.
  10. How to Start Thinking Like a Data Scientist by Thomas C. Redman (Nov 2013)
    You don’t have to be a data scientist or a Bayesian statistician to tease useful insights from data. The author demonstrates how to think with a small exercise.
  11. Stop Searching for That Elusive Data Scientist by Michael Schrage(Sep 2014)
    Stop hunting for that data science unicorn and/or silver bullet. What to do instead?
  12. How to Explore Cause and Effect Like a Data Scientist by Thomas C. Redman (Feb 2014)
    While we can use data to understand correlation, the more fundamental understanding of cause and effect requires more.