Big data has become a hot topic in the past five years or so, but it has been providing insights for hundreds of years. For example, the first U.S. census was taken in 1790, the Hollerith tabulating machine was created in the late 1880s, and in 1944 Fremont Rider was already envisioning that the Yale Library would have more than 200 million volumes by 2040.
Big data is undoubtedly big but is it also the big daddy of all things? There are many misconceptions associated with it and today we want to take you on a journey across these interesting myths
- Big Data is expensive – Big data solutions now exist that help you identify problems and react to them instantaneously, saving time and money. Services exist that allow you to only pay for the storage and computing capacity you actually use and yet give you the option to scale virtually infinitely. The reality is that your business can’t afford to not have these systems in place; data is your most valuable asset.
- BIG DATA IS MEGA USEFUL -Not all data is useful, and big data in its own purest unstructured form is perhaps the least useful. Unless we invest in organizing, processing and distributing it correctly (and perhaps associating packets of data) we will never find any insight or meaning of the big data. So when one is investing in Big Data, do care for a thought towards analytics and data mining and processing.
- BIG DATA IS BEST SUITED FOR BIG BUSINESS: You hear this common misconception all the time. But the truth is, big data technologies aren’t prohibitively expensive. So it’s not just for Fortune 500 companies, it can be used by much smaller businesses, too. Big data technologies are geared toward almost all industries as most companies produce a massive amount of data. So regardless of whether a business is large or small, there’s a good chance that they’re sitting on some data that can be useful.
- BIG DATA IS COMPLEX: Most companies start with infrastructure, software, and analytics tools before they have identified the business problems they are trying to solve. This results in costly investments, without any clear path to ROI. What businesses should do is that they should start with the key information needs of the Business/Marketing teams. If the marketing team can define and spell out key answers and key insights they need from Big Data, correctly or comprehensively, the IT teams can then structure the scope well and the whole enterprise benefits from the same
What do you think are the Biggest Myths or Misconceptions about Big Data? Let us know here in the comment section.
