The amount of capturable data people generate is truly mind-boggling, from commerce, health care, law enforcement, sports, and other domains. For example, according to one article, "Walmart controls more than 1 million customer transactions every hour..." The study of Big Data (also known as "Data Mining") applies statistical techniques such as correlation to discern patterns in the data and make predictions. Let's start with a brief video, listing numerous examples. Overview articles are available in the Harvard Business Review and on the Wikipedia (plus many other places I'm sure you can find via a Google search). A critique of the approach is available here.
Perhaps the most common use of Big Data is in the business world. A good entry point in this area is the book Supercrunchers by Ian Ayres. Probably the best-known story about Big Data is "How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did." What Target's statisticians did, essentially, was look for associations of whether customers' names were on the baby registry and whether they made greater purchases of certain products than the average person. Another potential business usage could come from this data-visualization of taxi and Uber trips in New York City (compare to layout of the city).
In the sports domain, I recommend three books pertaining to baseball: Moneyball (by Michael Lewis) on the Oakland Athletics; The Extra 2% (by Jonah Keri) on the Tampa Bay Rays; and Big Data Baseball (by Travis Sawchik) on the Pittsburgh Pirates. These three teams play in relatively small cities by Major League Baseball standards and thus bring in less local-television revenue than teams in bigger cities such as New York and Los Angeles. Therefore, teams such as Oakland, Tampa Bay, and Pittsburgh must use statistical techniques to (a) discover "deceptively good" players, whose skills are not well-known to other teams and who can thus be paid non-exorbitant salaries, and (b) identify effective strategies that other teams aren't using (yet). The Pirates' signature strategy, now copied by other teams, is the defensive shift, using statistical "spray charts" unique to each batter. (Major League Baseball later passed rules to limit shifting.)
One final book I would recommend is The Victory Lab by Sasha Issenberg on political campaigns, namely how candidates try to convince people to vote for them and get their supporters to actually vote.
To end the course, here's one final song...
Big Data
Lyrics by Alan Reifman
May be sung to the tune of “Green Earrings” (Fagen/Becker for Steely Dan)
Sales, patterns,
Companies try,
Running equations,
To predict, what we’ll buy,
Big data,
Lots of numbers,
Floating in, the cloud,
For computers,
To analyze, now,
We know, how,
Sports, owners,
Wanting to win,
Seeking, advantage,
In the numbers, it’s no sin,
Big data,
Lots of numbers,
Floating in, the cloud,
For computers,
To analyze, now,
We know, how
Instrumentals/solos
Big data,
Lots of numbers,
Floating in, the cloud,
For computers,
To analyze, now,
We know, how
Instrumentals/solos
