How easy is it to get lost in all the jargon that abounds in the business world? One might say easy as pie … but only if one is referring to eating pie, since making one from scratch is actually quite difficult.
How often have you observed people having a conversation about — or, more to the point, around — big data and/or business intelligence, and the more they talk, the more it becomes obvious that, although they are using the same lingo, they mean very different things from each other? Sometimes one person is confused, sometimes both are confused, and sometimes neither are confused — only using the terms to different ends.
Even on social media, the hashtag #BigData is used quite often and if you want a message to be seen by a larger audience you should use it. But we’re always hesitant because most of the information that we share (and most other companies as well) is really about Business Intelligence, not Big Data. And while #BI is a useful tag, there are some other non-business related messages that use #BI as well (we’ll leave that for you to discover).
There is a clear distinction between big data and business intelligence, and it’s important to know the difference because that knowledge could make a big difference to your company as big data and BI become less mere buzzwords and more everyday realities that every business must consider going forward.
We always advise, don’t let #BigData trick you into a solution with #BigCost.
Volume. Velocity. Variety. These are the three main properties defining big data, separating it from the data your company previously generated and could typically manage via old-school toolsets like Excel and FileMaker.
Big data is cool because it represents previously untappable insights that can potentially lead to major business improvements — game-changers for companies and even entire industries.
But big data in and of itself is still just data. There’s a lot of it, of course. Some of it will be relevant. But some of it won’t. And all of it means nothing without the proper analysis.
If big data were a piece of wood, business intelligence might be the ax that cut it and the artist who whittled it down to a figurine. BI is action. It means engaging with your information, whether regular-size or big data, and making something meaningful happen through it.
BI entails the organization and analysis of raw data to gain valuable business insights. It’s a Rosetta Stone that translates your information from meaningless symbols, strings of zeroes and ones, into a map that leads to business treasure: better decisions, greater efficiencies and higher profits.
Now that you have clarity on the two terms, the next logical step is to assess where your organization is at with respect to its data. Are you letting your big data sit around? Or are you turning it into valuable business intelligence? We hope you’re doing the latter. If not, though, request a demo of Yurbi to learn how you can get started.