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Demonstrating the Value of Big Data

Demonstrating the Value of Big Data

There can be no doubt that we are in the throes of a veritable Big Data explosion. Many companies, both large and small, are attempting to find ways to leverage value from their silos of unstructured data, through applied analytics techniques such as Natural Language Processing (NLP) and sentiment analysis.

However, due to its very nature, the science of extracting insights from repositories of Big Data is somewhat vague. This is because unlike structured data, where we know exactly what information we have, and in what format, Big Data is something of a pool with unfathomable depths. We don’t know how deep it is until we jump in and find out. For this reason, many companies are deterred from investing in extracting insights through analyzing Big Data. But there is plenty of proof to support the effectiveness of these data mining techniques.

For example, let’s take a look at some research findings published by Berkeley University regarding data volumes. Researchers at Berkeley University have published two utterly startling facts. The first of these is that the amount of data captured by commercial organizations doubles roughly every two years. Secondly, that an additional five quintillion bytes of data are generated and warehoused every two days. This is an incredible growth rate, and one that is bound to continue.

How does all this additional data help a company though? Does it have any real value? Of course it does, and Walmart has demonstrated this quite clearly. Early in 2013, Walmart applied advanced analytics techniques to the Big Data repositories that had been generated by its ecommerce site. The insights that Walmart managed to extract, allowed the company to extract an additional 15% of revenue from the same ecommerce site. In real terms, this represents an increase in revenue of some $1 billion.

Data scientists based the measurement of this growth in Walmart’s ecommerce sales by comparing revenue before the insights were actioned, and after. A very simple, logical way to measure the success of the Walmart Big Data project. The bottom line is that $1 billion is an awful lot of extra revenue, even for a company as large as Walmart. This demonstrates very well the power that is trapped within data silos, just awaiting some smart analytics to unlock its secrets.

Technology is evolving rapidly, and Big Data analytics is fast becoming one of the most viable ways for companies to gain the business insights required to start operating in a more consumer aligned way.