Unlocking the value in big data

CIOs should liken the management of big data to the innovation pipeline and consider the data's full life cycle

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Big data -- handling it, storing it and drawing value from it -- should be a big deal to CIOs.

One reason for this is the sheer volume of data being maintained by large enterprises. Last year, McKinsey & Co. concluded that it was not unusual for large U.S. corporations to have more data stored than the U.S. Library of Congress. How much data is that? Well, according to the library, its collection fills more than 800 miles of bookshelves.

And that data must be accessible if the companies acquiring it are to get real value from it. McKinsey last year also had something to say about just how much value big data could represent:

"... a retailer using big data to the full could increase its operating margin by more than 60%. Harnessing big data in the public sector has enormous potential, too. If US healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 billion in value every year. Two-thirds of that would be in the form of reducing US healthcare expenditure by about 8%. In the developed economies of Europe, government administrators could save more than ¬100 billion ($149 billion) in operational efficiency improvements alone by using big data, not including using big data to reduce fraud and errors and boost the collection of tax revenues."

Given all this, what steps should CIOs take to transform their IT infrastructures to take advantage of big data? I believe a good approach is to handle big data the way they manage innovation, as an end-to-end process. Innovation pipelines are intended to take ideas all the way from concept to execution for the ultimate realization of financial value. Big data can be viewed from a similar perspective: an information pipeline extending from data acquisition to access to availability to analytics -- the four A's of big data (see diagram). CIOs will need to transform their information infrastructures across all four of these areas and employ a life-cycle approach that combines big data and smart computing techniques.

big data model

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