Big Data isn’t Always Necessary – Three Questions to Ask

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On Wednesday, we raised an important question about big data. While analytics prove that everyone is talking about the topic, how many truly understand what it means? At this point, companies clamoring to make sure they’re prepared for the future might be concerned about whether or not their data is “big” enough. Many are ready to invest, but what if their plans are unnecessary or misguided?

If you can relate to that question, we have good news. “Big” data isn’t the answer for everyone. Because of the concept’s ubiquitous nature, it’s easy to assume otherwise. However, before diving headfirst down the big data path, ask these three questions of your company. They’ll provide direction and help you think about data in the right context.

1) Can my problem be answered by dark data I already have?

Most companies already have access to a lot of data that remains unused, or dark. Before investing in big data, it’s important to explore what underutilized data scores your company already has. There might be incredible untapped value right at your fingertips.

2) Do I have people on staff to manage big, unstructured data?

Later this month, we’ll help you figure out exactly who should handle data at your company. When it comes to investment, it might make sense to hire an expert who can optimize data you already have. Likewise, if you have employees who are somewhat qualified and offer multidisciplinary perspectives, providing further training for them might be key to your data success.

3) Do I really understand big data strategies and how to improve the optimization of information at my company?

Getting comfortable with the concept of big data before you make any decisions is crucial to maximizing its potential. Understanding exactly what it is and how it works will help you apply it to your company’s future. You might even find that for your company, maximizing the data you have, whether or not it’s “big,” is the fastest way to grow.

Stay tuned throughout February for more guidance on the path to data optimization.

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