What do we mean by 'Realizing business value from big data'?
Posting on behalf of Rajeev Nayar, Associate VP & Head, Big Data Practice
According to Gartner, about 64% of the companies have already invested in Big Data, and 56% have been struggling to derive value. This is something that we often hear when we talk about data, big data, analytics, reporting intelligence and so on and so forth. The question now is - 'Are enterprises really able to leverage the strength of data to start with and with deluge of data are enterprises able to leverage the strength of Big Data?'
When it comes to 'Realizing business value from Big Data' there seems to be a mismatch in how IT and business teams operate. Business teams wish to rapidly develop new insights and improve areas such as personalization, customer satisfaction; all irrespective of where the data lies. Technology teams traditionally are responsible in constructing a reporting mechanism to deliver these insights. This invariably has its own time lag from when the requirements were understood and to the time business team got the results. More often than not those results that they got were much later from when they actually needed it and it became irrelevant by the time the business teams actually got it. There is a significant mismatch in terms of how do we really look at this scenario of a structured IT construct and of the agility that the business needs and how we can help the enterprises leverage the strength of data in making right and timely decisions for their business expenses. Today, if we look at most enterprises, only about 20-25% of enterprise data is structured which has traditionally been used for analysis. 80% of data is unstructured. Only about 20% of data is traditionally used for analysis which is the structured construct.
What does an enterprise need to do when you look at this scenario?
First of all, the first big change is the scope of data itself. The scope with Big Data has changed from the traditional 20% structured construct that we have always been used to, to this large other 80% of unstructured data that has just become a part of the scope.
From the focus on data relationships, because structured data has always been based on the construct of established data relationships, the focus now shifts to understanding co-relations. The shift is happening from relying on data relationship which is known, to identifying correlations which are unknown in the past and that is really where the power of insights comes from.
And the third thing lies in identifying correlations moving away from data relationships, it's important to embed the element of discovery in the pattern of how you identify correlations. If you're not able to discover, you will minimize the element of identification of correlations.
Therefore the enterprises need to rethink their approach to Big Data first of all in changing scope of what data is meaningful to customers enterprise, secondly moving away from traditional data relationships to new correlations in business and to finally maximize correlations, enable technologies, enable frameworks that allows for self-discovery. And realizing business value lies in integrating these three pillars together.
Infosys Big Data services and solutions, have focused on helping enterprises to build a data ecosystem that empowers both technology and businesses to rapidly develop and action insights relevant to enterprises and customers business.