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    Top Five Questions to Answer Before Starting on Big Data

    As businesses begin to explore the insights, efficiencies and competitive edge Big Data can bring to their organizations, it is imperative they answer the right questions before getting too far down the road into a Big Data project, according to experts at ICC, a leader in business technology solutions focusing on Big Data and application development. “Big Data is many things but what it is not is a technology initiative. Your IT department will be deeply involved in setting things up and making sure you’ve got the number crunching horsepower to ‘do’ Big Data, but it is an initiative driven by the business not the IT department,” says Jim Gallo, national director of business analytics for ICC.

    Because Big Data is much more complex than simply managing and exploring large volumes of data, it is essential that organizations are reasonably assured their business needs and demands — improving customer loyalty, streamlining processes, improving top-line growth through predictive analytics, etc. — will be met before project spending begins.

     “As with any business decision about a new and emerging technology,” says Gallo, “if you answer a few basic questions beforehand, you will either set your Big Data initiative on a firm foundation, or conclude that it has no place at all in your organization.”

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    Click through for five questions any organization considering a Big Data initiative should ask before beginning, as identified by ICC.

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    Rather than focusing on technology, your Big Data initiative should begin by addressing how it will help your organization achieve its business objectives, whether improving efficiencies, increasing margins, or attracting a deeper share of wallet.

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    Once you’ve defined the business case you have to determine what this means from a data perspective. Just because a data set is large, that doesn’t automatically make it “Big Data.”

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    Once you’ve determined you do have a Big Data need, you have to identify potential data sources. The information you’re after may take some serious integration work to capture or may have to be brought in from third-party sources like social, weather, video, sentiment, or public data sets, for example, or it may not exist at all.

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    Define the value you will get from Big Data first. Corporate decision-makers faced with escalating costs, shrinking budgets and conflicting priorities are not going to fund a solution without a solid business justification with solid ROI. That’s why you ask the “What do you want to know?” question first.

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    There is much to consider before embarking upon a Big Data initiative, so a healthy dose of skepticism should be employed at every step of the process. Don’t do Big Data for the sake of Big Data. The stakes can be high relative to costs and benefits, so it’s best to have a reasonable assurance that choices you make will deliver.

    So above all be prudent and make sure there’s a need, that the problems are business-focused and clearly defined, that they are solvable, and that a positive ROI is attainable. Once these conditions are met, go for it! Done right, Big Data can translate into big value.

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