An Apologia for People. Big Data Are Just Peachy Keen
December 25, 2016
I read “Don’t Blame Big Data for Pollsters’ Failings.” The news about the polls predicting a victory for Hillary Clinton reached me in Harrod’s Creek five days after the election. Hey, Beyond Search is in rural Kentucky. It looks from the news reports and the New York Times’s odd letter about doing “real” journalism that the pundits predicted that the mare would win the US derby.
The write up explains that Big Data did not fail. The reason? The pollsters were not using Big Data. The sample sizes were about 1,000 people. Check your statistics book. In the back will be samples sizes for populations. If you have an older statistics book, you have to use the formula like
Big Data doesn’t fool around with formulas. Big Data just uses “big data.” Is the idea is that the bigger the data, the better the output?
The write up states that the problem was the sample itself: The actual humans.
The write up quotes a mid tier consultant from an outfit called Ovum which reminds me of eggs. I circled this statement:
“When you have data sets that are large enough, you can find signals for just about anything,” says Tony Baer, a big data analyst at Ovum. “So this places a premium on identifying the right data sets and asking the right questions, and relentlessly testing out your hypothesis with test cases extending to more or different data sets.”
The write up tosses in social media. Facebook takes the position that its information had minimal effect on the election. Nifty assertion that.
The solution is, as I understand the write up, to use a more real time system, different types of data, and math. The conclusion is:
With significant economic consequences attached to political outcomes, it is clear that those companies with sufficient depth of real-time behavioral data will likely increase in value.
My view is that hope and other distinctly human behaviors certainly threw an egg at reality. It is great to know that there is a fix and that Big Data emerge as the path forward. More work ahead for the consultants who often determine sample sizes by looking at Web sites like SurveySystem and get their sample from lists of contributors, a 20 something’s mobile phone contact list, or lists available from friends.
If you use Big Data, tap into real time streams of information, and do the social media mining—you will be able to predict the future. Sounds logical? Now about that next Kentucky Derby winner? Happy or unhappy holiday?
Stephen E Arnold, December 25, 2016
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