Big Data Is Just a Myth
August 1, 2016
Remember in the 1979 hit The Muppet Movie there was a running gag where Kermit the Frog kept saying, “It’s a myth. A myth!” Then a woman named Myth would appear out of nowhere and say, “Yes?” It was a funny random gag, but while it is a myth that frogs give warts, most of the myths related to big data may or not be. Data Science Central decided to explain some of the myths in, “Debunking The 68 Most Common Myths About Big Data-Part 2.”
Some of the prior myths debunked in the first part were that big data was the newest power word, an end all solution for companies, only meant for big companies, and that it was complicated and expensive. In truth, anyone can benefit from big data with a decent implementation plan and with someone who knows how to take charge of it.
Big data, in fact, can be integrated with preexisting systems, although it takes time and knowledge to link the new and the old together (it is not as difficult as it seems). Keeping on that same thought, users need to realize that there is not a one size fits all big data solution. Big data is a solution that requires analytical, storage, and other software. It cannot be purchased like other proprietary software and it needs to be individualized for each organization.
One myth that is has converted into truth is that big data relies on Hadoop storage. It used to be Hadoop managed a market of many, but bow it is an integral bit of software needed to get the big data job done. One of the most prevalent myths is it only belongs in the IT department:
“Here’s the core of the issue. Big Data gives companies the greatly enhanced ability to reap benefits from data-driven insights and to make better decisions. These are strategic issues.
You know who is most likely to be clamoring for Big Data? Not IT. Most likely it’s sales, marketing, pricing, logistics, and production forecasting. All areas that tend to reap outsize rewards from better forward views of the business.”
Big data is becoming more of an essential tool for organizations in every field as it tells them more about how they operate and their shortcomings. Big data offers a very detailed examination of these issues; the biggest issue users need to deal with is how they will use it?