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Splunk Digs Into the Year of the Big Data Application

Big Data: Not Just for Big Business Anymore If 2013 was the year that most organizations discovered what Big Data platforms such as Hadoop were all about, then the coming year will be the one in which they discover the applications that turn all that data into something of business value. Brett Sheppard, director of […]

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MV
Mike Vizard
Jan 2, 2014
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Big Data: Not Just for Big Business Anymore

If 2013 was the year that most organizations discovered what Big Data platforms such as Hadoop were all about, then the coming year will be the one in which they discover the applications that turn all that data into something of business value.

Brett Sheppard, director of Big Data marketing for Splunk, says that in terms of Big Data, 2013 was pretty much defined by investments in plumbing. Organizations largely experimented with Big Data platforms only to discover that the cost of acquiring the platform was nothing compared to the cost of the expertise required to actually develop an application that could make sense of all that data.

But with the rise of Big Data applications such as Splunk Analytics for Hadoop, Sheppard says 2014 will be the year that the average business user discovers packaged applications that will substantially reduce the amount of time it takes to get a return on investment in Big Data. Instead of waiting months, even years, for the internal IT organization to create a custom application, Big Data applications will be readily available.

Those applications, says Sheppard, will substantially reduce the reliance on data scientists, who are not only in short supply but are also fairly expensive to hire. Instead, business users with a sense of curiosity will be able to interactively explore sets of data at will, without having to wait for the IT organization to generate a report.

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Whether it involves traditional business applications or a new generation of analytic applications using machine data generated in one way or another by The Internet of Things, Sheppard says we should be able to more easily identify anomalies and predict future events by analyzing the long tail of machine data without necessarily having to understand every nuance of the data lifecycle.

Of course, what will be interesting to see is which businesses in 2014 turn that potential into an actual business advantage. After all, having a new tool is one thing; understanding how to apply it is often quite another thing altogether.

MV

Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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