Monday, July 29, 2013

Big Data vs Business Analytics?

Big Data can change your world and we aim to tell you how over the next few weeks.
But before we get into that, lets take a step back and understand what the terms surrounding Big Data really mean.

Big Data, Business Analytics, and Business Intelligence are terms that are generally used to refer to processing data.

But is ‘big data’ just another way of saying ‘business analytics’?

The answer is an emphatic NO



Wikipedia defines Business Analytics as the “discovery and communication of meaningful patterns in data”. Business analytics has been in use since the late 1960s, when computer based information systems were used to support decision-making activities. Firms commonly apply analytics to business data, to describe, predict, and improve business performance.


For instance, Banks have long been using business analytics to differentiate customers by characteristics such as credit risk and usage. Similarly, Financial services firms have been using analytics to identify future growth trends on the basis of historic data.

Business Analytics needs data to identify trends. But the traditional business analytics software struggles with Big Data. Its tools were not designed to sift through massive data warehouses storing enormous data in a variety of different formats. Millions of dollars and enormous amounts of time and energy have been spent to develop these software programs, but it is still a Herculean task to identify meaningful data and ignore the useless bits.

The term Big data is self explanatory – it is literally data that is too big to be handled by conventional data management softwares. According to Edd Dumbill of O’Reilly media, Big Data is defined as “data that exceeds the processing capacity of conventional data processing systems. The data is too big, moves too fast, and doesn’t fit the structure of conventional database architectures. To gain value form this data, you must choose an alternative way to process it.

In the coming posts we will start digging deep into the big data universe and explore other aspects of the big data landscape…

Stay tuned!

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