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One of the biggest reasons Big Data is so misunderstood probably has to do with its name. It’s ambiguous, invites debate, and seems as if it’s all about being just a “whole lot of data.” But that couldn’t be farther from the case, and because of these misconceptions, a lot of organizations aren’t getting it right when it comes to establishing successful Big Data initiatives.

Big Data expert and influencer Bernard Marr wrote a great post over at Forbes today on the subject, “5 Telltale Signs You Don’t Understand Big Data,” which are that companies:

  1. Ignore Big Data
  2. Think Big Data is only about data
  3. Think that it’s only about huge quantities of data
  4. Think the more data flowing in, the better
  5. Think big data means you need to store large amounts of your own data

Out of all of these points Marr makes, I’d argue that ignoring the Big Data wave is the most egregious, purely because Big Data is still a (pretty big) thing (not going anywhere anytime soon), and leaving insight on the table that could propel your business forward seems like a recipe for mediocrity and lots of missed opportunity.

If I were to reword Marr’s sign of “ignore big data,” though, it would be something along the lines of “Acknowledge Big Data is a big deal, but don’t have the means at this time to make the big investment.” After all, as Matt Turck of FirstMark, a VC firm, notes, taking advantage of Big Data is hard work: “Big Data success is not about implementing one piece of technology, but instead requires putting together an assembly line of technologies, people, and processes…the entire company, starting from senior management, needs to commit to building a data-driven culture, where Big Data is not ‘a’ thing, but ‘the’ thing.”

The most universally shared misconception of Marr’s list would arguably be that Big Data is only about “huge volumes of data” (it is called Big Data, afterall), as Marr notes:

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…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.

Perhaps, Big, Complex, Much Variety of Data doesn’t roll off the tongue as much as Big Data does.

I recommend checking out the full post because it’s a fun read, but in the meantime, do you agree with these five misconceptions? Where else are companies striking out when it comes to their own misconceptions about Big Data? Let us know in the comments below or on Twitter at @BigDataProABG.

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