“The ultimate challenge… is putting enough useful Big Data capabilities into the hands of the largest number of workers. The organizations that figure out this part will reap corresponding rewards.” Dion Hinchcliffe’s recent post “The enterprise opportunity of Big Data: Closing the ‘clue gap'”.
Sorry to sound like Ebenezer Scrooge of Dickens’ “A Christmas Carol”, but… Bah, humbug!
Some business users have been doing analytics for years… in Excel. Do we consider that an Information Management success story? Have the business benefits far outweighed the costs in terms of users’ time, IT’s efforts in trying to provide data or, indeed, the numerous spreadsheet-induced business mistakes and mis-stated statutory reports? In a word, no!
So, what do you think? Will providing growing volumes of increasingly diverse data through ever more sophisticated and speedy statistical analysis tools make this situation better or worse? Furthermore, does every user want or need to be a statistician?
I believe that we are in danger of being caught on a hype wave here. Extreme analytics and big data certainly have an important role to play in modern business. But that role is in exploration and innovation of new opportunities for or threats to the business. For many managers, regular reports and the ability to drill down into exceptions and outliers are as much as they need. In other words, traditional BI. For much of the business, the focus is on the minutiae and the mundane. For daily decisions–and such decisions are the heartbeat of the business–the information required and the implications of the vast majority of possible circumstances are already largely known. Big data and extreme analytics are unnecessary. What is required is faster access to current transaction data or easier access to background content.
We’ve known this fork in BI for many years. It’s the difference between tactical/strategic and operational BI. And while analytics and big data are getting the publicity, much is going on to restructure and re-architect the foundations of traditional BI. One of these advances is data virtualization.
The emergence of big data has, of course, made data virtualization a mandatory technology for BI. Given the volumes of data involved, it makes less and less sense to duplicate data on the scale we do it today. And reduced duplication means that remote access, federation, EII or whatever term you like becomes a key component of any modern BI architecture. I’ll be discussing this at the kickoff webinar today of Denodo’s Data Virtualization World Series, available also on-demand from B-eye-Network.
So while we’re dreaming dreams of extreme analytics and big data in Christmas’ Future, let us also keep our eyes firmly fixed on Christmas Present and how we meet the current needs of the majority of ordinary business users.