Despite the fact that I bill myself as a “big data” expert, I wish we could come up with a better term. If you’re not sure what I’m talking about, you’re not alone. Here are five of the biggest misunderstandings about big data I see regularly:
You ignore big data.
Bad move. Data and the ability to turn data into business value will become increasingly important in any sector within a few very short years. In business, information is power, and big data is providing information we couldn’t have dreamed of collecting or analyzing just a few short years ago. Practically every field and every job within them, from untrained hourly worker all the way up to professionals, can expect the business landscape to be changed by data in the near future. Ignoring it is sticking your head in the sand; this is a trend that is not going away.
You think big data is about data.
Interestingly, it is not; it’s about what you do with it. I’ve long argued that simply collecting data or even analyzing it isn’t the end game of a big data strategy. Instead, it’s about how you use the information you glean from the data. It’s about the processes you improve, the decision making you enable, the business value you add. Data for data’s sake is meaningless. Without valuable interpretation and smart implementation, big data projects are a costly and ridiculous waste of time.
You think big data is about quantity.
Big data got its name because advances in technology seemed to quite suddenly allow us to collect and analyze much greater quantities of data than ever before. But part of that was also because we gained the ability to analyze new types of data — especially unstructured data. Before, the only useable data was the kind that fit neatly into the rows and columns of a database. Today, we can analyze large blocks of text, like books and journals, video, photos, audio, health records, and more. So big data isn’t just about the volume of data; it is equally about the variety of data to which we now have access.
You think the more data you get your hands on the better.
Some companies have become data hoarders, collecting and storing as much data as they possibly can against the future chance that they might need it. But this quickly becomes a very costly enterprise. Data storage isn’t free, and as the size of your “collection” grows exponentially with every year, so does the cost. In addition, searching and analyzing those vast quantities of data become more challenging and require more resources. Instead of hoarding data, collect only what you really need and what makes business sense. I always advocate understanding the questions you want to answer before designing a big data project so that you can remain lean and focused on the outcomes.
NOTE CREDIT: http://www.forbes.com/sites/bernardmarr/2016/05/19/5-telltale-signs-you-dont-understand-big-data/#554448a82c70