Now, well into 2013, the concept of Big Data is already becoming an outdated non sequitur. As data increases rapidly, storing huge amounts of data in uncorrelated, separated silos (in database or data warehouse storage) that need to be constantly queried can’t drive any new, intelligent change in a business. In fact, this approach creates even greater challenges. Big Data by itself can’t drive change because it is just a more efficient, more technological way of doing business as usual. Databases that store transaction history are a practice as old as a shop keeper maintaining a ledger of purchases and sales. How is simply scaling that same idea into the millions of entries going to drive any real change in business? That old approach is Big Data 1.0 and it can’t compete with correlated, referential Big Data. Integrating varied information in an individual context, in the moment of customer’s engagement is fundamental to move business forward in any way and has to be the foundation of any conception of Big Data 2.0.
The Process of Storing and Using Big Data is Inherently Limiting
If data is stored and siloed on a system-by-system basis, like transaction history in its own isolated database, all the petabytes in the world won’t give any real business advantage. Trying to gain understanding of customers, suppliers, or partners from transaction data in isolation, even if it’s every piece of transaction data from a company’s founding, is a one-dimensional approach with one-dimensional results. [Read more...]
