A recent opinion piece in the NY Times takes a look at the strengths and weaknesses of data analysis and the use of such analysis in making business decisions. Big Data is currently the buzzword in venture capital circles, and money is flowing to companies that collect and analyze huge volumes of data. But arenít there some things that data just canít do?

As the author suggests, data can report numbers of social interactions, but not the actual quality of those meetings. Does the fact that you meet with a co-worker several times a day mean that you enjoy spending time with them more than your friends?

Data can record events, but canít provide context. When you buy a book on the Internet, is it because you want to read it? Or is it because you want to give it to a friend at an upcoming birthday party? Should the bookseller now inundate you with offers for similar books, not knowing exactly why you bought what you bought?

It is pointed out that data is never truly raw, as it has to be structured in some way in order to be interpreted. This means that the structure can have an impact on the result. It reminds one of the quantum physics theory that once an event is observed, it has changed because of the perception of the observer.

In fact, the more data that is compiled the bigger the data set and the more correlations that can be derived. Not all of the correlations will be germane to a specific challenge or strategy, and only intuitive human analyses can accurately sort and value data-driven decision possibilities.