Falsehoods of business data analytics: 3 myths busted
Mar 31, 2015
Business data analytics – or, as it is more commonly known, big data - has seen a considerable amount of attention in the last few years. Companies have heard myriad rumors surrounding how big data can be utilized to highlight actionable insights from the information that the organization already has on hand, not to mention all the benefits that can follow.
However, with all the truths circulating throughout the corporate world, there are just as many falsehoods. Decision-makers have been told a number of incorrect “facts,” which has affected how they approach their business data analytics strategies. Let’s take a moment to address these myths and set the record straight, once and for all.
Myth: Big data isn’t big data if it isn’t big
Okay, a bit confusing, but the bottom line here is that administrators have been told that if their information sets are huge and expansive, they won’t be usable in business data analytics. However, as ITWeb contributor Gary Allemann pointed out, this is completely untrue. It’s not the size of the data set that makes an initiative effective, it’s how this information and the resulting analytics are put to use.
“Use cases…may not require vast amounts of data,” Allemann wrote. “Rather they require the ability to bring together both structured and unstructured data to answer the question.”
In some situations, especially those where the end goal is a very specialized or focused insight, the less data that is included in analytics, the better. Too much information can become increasingly hard to work with and can create huge headaches for users. In this way, big data doesn’t always have to be big.
Myth: If you don’t jump on the big data bandwagon now, you’ll be left behind
The buzzword status of business data analytics processes have some thinking that if they don’t start gathering and examining all the information they can as quickly as they can, they’ll fall behind their market competitors. However, Opera Solutions CEO Arnab Gupta told InformationWeek that it’s this kind of thinking that can put companies in a sticky situation. Before administrators even have an idea of what they’ll do with all the data, they have teams of employees collecting it at light speed. Business data analytics initiatives need proper planning and a defined set of goals in order for them to do any good for the organization.
“The problem with first vs. last thinking is that you assume that if you’re first, you’re going to get a competitive advantage, but that won’t be the case if you don’t focus business results that will give you a business advantage,” Gupta noted.
Myth: If it isn’t organized, it isn’t usable
This is another falsehood running rampant throughout the corporate world: Naysayers have decision-makers believing that their unstructured data has to be strictly compartmentalized and arrang