data-analytics
Business Management

Jim Gallo (Global) - Big Data is About the Business Not the Data

If you can't articulate why you need big data, then maybe you don't.

Big data is everywhere today. It's impossible to open any industry trade publication or click on a technology website without "Big Data" showing up front and center.

There are many reasons for this-the hype cycle, cheap storage, and Hadoop, are a few of the easy ones that come to mind-but really, the reason Big Data is such a hot topic is because of the actionable intelligence and insights businesses will soon be using to open new markets and explore existing markets further. Or getting a bigger share of their customer's wallet, if you will.

As businesses begin to explore this new world, however, it is very important they answer the right questions before jumping on the Big Data bandwagon. As I've said many times, Big Data is many things but it is not a technology initiative. Your IT department will definitely need to be involved, but Big Data is a business initiative.

Because Big Data is much more complex than simply managing and exploring large volumes of data (the first of the three "Vs" of Big Data - volume, velocity and variety), it is crucial that organizations be reasonably assured their business needs-improving customer loyalty, streamlining processes, improving top-line growth through predictive analytics, etc.-will be met before you spend a nickel.

If you answer a few basic questions beforehand, you will start your Big Data project off on the right foot.

Top 5 Big Data questions to answer

  1. What do you want to know? Rather than starting with tech, your Big Data project should begin by addressing how it will help your organization achieve business objectives.
  2. Do you have a "Big Data" problem or a "lots of data" problem? Just because a data set is large, that doesn't automatically make it "Big Data." You'll need to figure this out.
  3. Where will the data come from? 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. You'll need to identify these sources beforehand.
  4. Is it worth it? Executives faced with escalating costs, shrinking budgets and conflicting priorities are not going to fund a solution without a business case and solid ROI. That's why you need to ask the "What do you want to know?" question first.
  5. Will it work? Ah, the $64,000 question. There is much to consider about Big Data, 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, then, go for it! Done right, Big Data can translate into Big Value.

 

By Jim Gallo, National Director, Business Analytics, ICC (Information Control Corporation)

 

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