What Is A Successful Big Data Strategy
In general, dealing with datasets means enterprises are looking at drawing meaningful patterns that are expected to offer useful insights to build their business. From structured to unstructured, data is varied and analyzing it is not only complex, but requires an effective big data strategy.
The global market for big data is expected to grow from $14.8 bn to $46.3 bn by 2018, at an estimated CAGR of 25.52 percent during the forecasted period (Marketsandmarkets)
Certainly, big data is not just about an enterprise’s storage capacity, it is how data is used as a tool for decision making. Expectations about big data are as varied as its structure.
“There is a big data revolution,” says Weatherhead University Professor Gary King in Harvard Magazine. But it is not the quantity of data that is revolutionary. “The revolution lies in improved statistical and computational methods, not in the exponential growth of storage or even computational capacity,” he says.
Analysts have found out many businesses still do not know what to expect from big data and they lack a clear understanding of how to derive benefits from it. As Sumeet Tandure, Regional Head - Platforms, Solutions & Services, HDS states: “the challenge is to determine where to look for the right data sets, how to extract meaningful insights from the glut of information that exists and how to interpret this in the right context.”
Making the right data decisions requires business acumen and an understanding of critical areas for investments. Despite the growing hype around big data, enterprises are yet to understand what suits them the best.
A survey conducted by data discovery and analytics solution company Qlik among 350 executives based in key Indian cities found that while only 21% of respondents say they have implemented Big Data technologies, 42% said they plan to invest in Big Data technologies in the next 12 months.
Richard de Souza, Vice President Corporate IT, Head Business Solutions, Mahindra Group believes that it is not enough for a company to mindlessly store away data. “IT departments have already started investing in enterprise data warehouses and legacy solutions; however very soon they will be focusing on investing in the right solutions to analyze Big Data,” he says.
A Gartner study in September 2014 found that 73% had invested or plan to invest in big data in the next 24 months, up from 64% in 2013. On the investment side, the signs are positive, but the basic problem seems to be with what comprises a big data strategy and what shapes a big data investment plan.
A strategy must align with the business goals. Apart from reorganization of data architecture, it could also include implementing data-governance standards that systematically maintain accuracy, says McKinsey.
There is a need to have two plans—long-term and short-term, so as to define the requirements for businesses.
Nick Heudecker, research director at Gartner, feels most organizations don’t have a plan for what they’re going to do next. “Picking everything isn’t a strategy. It indicates a fear of missing out on an opportunity yet to be defined.” He advises organizations can ‘do big data’ on transactions and log data, so that they may assume they can also leverage more challenging data sources as easily.
What is essential for enterprise is to identify business areas where big data will have the greatest impact. An IDG survey found that majority of big data investment is in storage (49%) followed by servers (47% ) and analytics (43%).
Once the areas are finalized, enterprises face bigger challenge in terms of deciding the kind of solutions, which are increasingly becoming complex due to the growth of data crossing boundaries.
A Marketsandmarkets report says the solutions available for big data are complex in nature and difficult to understand. Hence the companies are unable to implement these solutions. But on the other hand, there has been an emphasis on end-to-end business processes to fully integrate analytical models and enhance the data management capabilities to optimize performance.
A big data strategy must begin with enterprises defining the business vision and it is not just the prerogative of the IT department.
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