What’s the Big Deal about Big Data? Exciting Data that is Useless Without Analytics

aGary King, the director of Harvard’s Institute for Quantitative Social Science, was trying to track down the provenance of figures about AIDS in Africa when he discovered that the ”official” numbers were actually just estimates made by a man named Alan. Alan’s numbers were actually pretty good, King added, but it wasn’t empirical or scientific. Now, he suggested, through Big Data we can do better than educated guessing.

Alan’s story is one of many examples cited by King in a talk he made this summer on Capitol Hill in Washington, D.C. to an audience filled with policymakers and fellow academics. The event was hosted by SAGE Publishing with co-sponsors the American Political Science Association and the American Statistical Association.

In a series of 10 videos from that event, titled “The big deal about big data,” King hammers home two themes: First, it’s not the data itself that’s revolutionary, but the analysis of it. “The value is not the data,” he says. “It’s not the big, it’s the analytics.” And second, the data revolution’s outputs are genuinely, well, revolutionary, as his examples demonstrate.

In the third of those videos, King opens by asking about exercise, and noting that the continuous data provided by cell phones and FitBits is much more valuable than even large-scale efforts at self-reporting. However, in keeping with underlying message, King insists that the data itself isn’t what’s truly valuable,  it’s the novel analysis of what the data can tell us. Comparing a sleeping passenger on Amtrak whose accelerometer keeps notching strides from the bumpy ride to the all-out cyclist on a stationary bike getting generating no data for the phone, he explains, “You need the analytics to interpret the data properly.”

He then cites other examples –harvesting the opinions of activists, or determining  a person’s network of social contacts – as situations where purely qualitative approaches of the past are vastly enhanced by quantitative means – but only when intelligent analysis is involved. Otherwise, he asks, “What are we supposed to do with that information?”

Videos in the series

  1. Ziyad Marar On The Opportunities That Big Data Provides Social Scientists
  2. What Makes Big Data Valuable?
  3. Examples: Exciting Data That Is Useless Without Analytics
  4. Example: Social Scientists Determine Cause Of Death At A Distance
  5. Example: Analysis Rids Social Security Forecasts Of Bias
  6. Example: New Data Methods Combat Gerrymandering
  7. Example: Big Data Much Better Than People At Determining Keywords
  8. Example: Watching Chinese Citizens Get Around Censorship
  9. Example: Learning The Real Reason For Chinese Censorship
  10. The Spectacular Success Of Quantitative Social Science

 

     
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