Is small beautiful?
When I think of Big Data, I am thinking how BIG it needs to be before it can be useful. This week's reading on Insurers and the work done by Levitt and Dubner on Freakonomics tells us clearly that data not earlier thought relevant or causal can be an efficient predictor.
Secondly, strategies designed on BIG data (telephone usage follows a power law implies we should take out small sized recharge coupons) may overpower small data strategies (enable a community of 5 friends to communicate at lower prices).
Thirdly, BIG data also has BIG impacting factors. For example, mobile number portability has come in to India today. It will shift individual company demographics and usage data, as well as impact mobile phone usage patterns. For some BIG data, policy decisions, technological differences et al will make a vast difference. You can homogenize who-called-who-and-where-and-when but that robs the context and obscures the diversity. Similarly, BIG analytics, robbed of context, cannot predict negative reactions of a strategy which does not provide for any contingency planning.
Fourthly, actions taken on BIG data will have big consequences, perhaps rendering the initial analytics obsolete - would BIG analytics follow the Heisenberg principle?
Lastly, if everybody, big or small, started using BIG analytics, to make decisions (say on customer profiles in the XYZ insurance segment), companies would anyway lose the competitive differentiator that analytics brings to them.