Donald Feinberg, VP and analyst at Gartner’s Intelligence and Information Group, recently said that Big Data will die within the next couple of years, thanks largely to the confusion which surrounds the term.
Once upon a time, databases were relatively small; tiny by today’s standards. Businesses had records of their customers’ accounts, built up manually over time, originally with pen and paper and later with microprocessors. Bigger companies started to have whole floors dedicated to data processing departments, ensuring that purchase orders and invoices we all matched and accurate, and accountants knew who had paid and who owed money, what had been bought and what had been cancelled.
With cloud computing and processing technology getting so small that you could practically map out the life cycle of a grain of rice, data started to get recorded and collected at increasingly faster rates and much more of it. Processors in cars and other equipment meant that a whole boatload of parameters could be constantly measured.
More and more measurables
Social media sites, ecommerce sites and other communal online gatherings meant that individuals could be adding to the pile of data already stored about them as they filled in forms and registered for things online. Photos, likes, friends, birthdays, political leanings, sexual orientation, marriage status, hobbies and interests…the list of measurables became endless.
Marketers cottoned on that they could find out even more about people and their activities by giving a little entertainment in return for information.
Data was evolving and its new buzz-name was emerging. This thing was big and needed a grand, although quite unoriginal, title. ‘Big Data’ was born and every smart sales person, IT geek and technical consultant around was throwing the phrase around in conversations.
What to do with Big Data?
Some people had ‘Big Data’ but didn’t know what to do with it. Others had bigger ‘Big Data’ than everyone else (so there) and knew exactly what they wanted to do with it. Certain eager beavers didn’t care if it was called Data, Big Data or naught and one spaghetti; they just made sure that the IT infrastructure for their organisation could handle any amount of information that was going through their servers and conduits.
Others blissfully got on with running their businesses, hiring the services of IT support companies and other professionals who would make sure their systems didn’t crash and their printers worked when they turned them on. Some smart people were figuring out how to condense meaningful understanding from all the data they were gathering.
This was Big Data’s heyday, and a time when it actually meant something. Technology was changing and much of the change related to the amount of data that was ‘out there’, how it was being managed, how quickly it could be processed and moved around, and the mind-blowing variety of variables that could be and where being measured. Surely this data was going to be extremely useful for managing situations, for making the most out of the trends, for future proofing organisations by learning lessons from the past.
In fact, the enormity of the situation meant it was almost beyond definition. From a business perspective many aspects of how information stock piles were growing could be a threat or an opportunity. It all depended on how businesses reacted to the changes and the trends, and embraced what was happening. There would be winners. There would be losers. Who would win and who would lose was down to how they played the Big Data lottery.
The death of Big Data?
Yes, they were halcyon days for ‘Big Data’, so what changed? How did Big Data eventually get sick, and then subsequently die? What went wrong? In a nutshell, it was beaten by its own success. It was made redundant by its own arrival.
Big Data could be seen as a hurricane on its way to a land that has never experienced such a phenomena before but is going to imminently – where people are forewarned well in advance that there is a disturbance in the weather, troubled times ahead, that the time is coming to baton down the hatches and seek cover before the incredible winds, rain and destruction arrive. The time for talking about it, for describing, defining it and giving explanation is before the storm hits. Once the storm hits, everybody is too busy making sure they come out on the other side in one piece.
A major change in how information was being generated and gathered was occurring that required attention and action on a number of fronts. Just as the village needed to be prepared for the high winds of the hurricane and in order to be convinced that it was coming, it was defined, described and explained to them; so was Big Data the catch-all solution to capture the revolution in data processing.
That job has been done. Mentioning Big Data is now pointless. The consequences of its arrival are already here in the flesh. Businesses are finding right now that they either have control of the information in their possession or they don’t. They are either benefitting from the intelligent analysis of the information that counts or they have been focusing on the least fruitful facts and figures – or maybe not mining from their data banks effectively at all.
Big Data was a hype word. It was a necessary one to galvanise people into action, to facilitate communication and sum up a range of phenomena that needed to be acknowledged – like the ‘swinging 60s’, but now the realities have already hit home the people who are really in the know are looking for the next change they need to predict. Big Data is rapidly becoming a ghost that is only mentioned by people who are not so savvy, or who are desperate to show understanding in order to sell a product or service.
Thanks for everything you did for us, Big Data. Good bye and God bless. May you rest in peace.
Image: Gerd Leonard