Saturday, May 18, 2013

Big Data: A Revolution That Will Transform How We Live, Work, and Think.

Takeaways from the book written by Viktor Mayer-Schonberger and Kenneth Cukier.


  • Google could project the spread of the winter flu in the United States, not just nationally, but down to specific regions and even states. The company could achieve this by looking at what people were searching for on the Internet.
  • Data has become a raw material of business, a vital economic input, used to create a new form of economic value. In fact, with the right mindset, data can be cleverly reused to become a fountain of innovation and new services.
  • Big data is all about seeing and understanding the relations within and among pieces of information that, until very recently, we struggled to fully grasp.
  • The concept of sampling no longer makes as much sense when we can harness large amounts of data. Hence Google flu trends doesn't rely on a small random sample but instead uses billions of Internet search queries in United States.
  • For a long time, random sampling was a good shortcut. It made analysis of large data problems possible in the pre-digital air. But much as when converting a good digital image or song into a smaller file, information is lost when sampling.
  • Using all available data is feasible in an increasing number of contexts. But it comes at a cost. Increasing the volume opens the door to inexactitude. 
  • Big data, with its emphasis on comprehensive data sets and messiness, helps us get closer to reality that did our dependence on small data and accuracy.
  • Correlations are useful in a small Data-world what in the context of big data they really shine.
  • Today a third of all Amazon sales are said to result from its recommendation and personalization systems. 
  • Following Amazon's  lead, thousands of websites are able to recommend products, content, friends, and groups without knowing why people are likely to be interested in them.
  • To determine how likely people are to take their medication, FICO analyzes a wealth of materials including ones that may seem irrelevant, such as how long people have lived at the same address, if they are married, how long they've been in the same job, and whether they own a car.
  • Target knows what a woman is pregnant without the mother to be explicitly telling it so. Basically, it's method is to harvest data and let the correlations do their work. Targets marketers turned to its analytics division to see if there was a way to discover customers pregnancies through their purchasing patterns. the Target team ultimately uncovered around two dozen products that, used as proxies, enabled the company to calculate a pregnancy prediction score for every customer who paid with a credit card or used their loyalty card or mailed coupons.
  • The shipping company UPS has used predictive analytics since the late 2000s to monitor its fleet of 60,000 vehicles in the United States and know when to perform preventative maintenance.
  • What makes the Decide.com special isn't that the data: the company relies of information it license from E-commerce sites and scrapes off the Web, where it is free for the taking. What makes Decide.com special is the idea: the company has a big data mindset. It spied an opportunity and recognized that certain data could be mined to reveal valuable secrets.
  • MasterCard discovered, among other things, that if people fill up their gas tanks at around 4 o'clock in the afternoon, there are quite likely to spend between $35 and $50 in the next hour in a grocery store or restaurant. As a middleman to information flows, MasterCard is in a prime position to collect data and captures you. One can imagine a future when credit card companies forgo their commissions on transactions, processing them for free in return for access to more data, and earn income from highly sophisticated analytics based on it.
  • Statisticians are supplanting scouts in baseball ( Moneyball book by Michael Lewis). The subject matter expert, the substantive specialist, will lose some of their luster compared with the statistician and data analyst, who are unfettered by the old ways of doing things and let the data speak.