History Doesn’t Repeat Itself – It Rhymes
Back in the early '90s there was no doubt that the internet was going to change how we did so many things. But it asserted itself in a much slower manner than the pundits were stating at the time and it was not without its trials and tribulations, which saw catastrophic carnage resulting from the dotcom fallout.
We have learned many lessons from those days but I fear as I review the headlines and speak to so many people, there is a whiff of froth that will result in a few scalps.
Big Data is without a doubt the future, we completely buy into it but as it is young, there remain important gaps to close. The economics are not proven and, for us early adopters, a cautious pragmatic approach is probably wise.
If you are toying with the idea, may I highly recommend you read Wayne Eckerson’s “Secrets of Analytical Leaders.” It’s a really great study, and insight into how half a dozen analytical leaders have sequenced in Big Data and how they are bringing it to bear.
Big Data will do to analytics what dotcom did to business. It will result in new business models emerging, new insights and therefore new behaviors, the white faced long haired PhD students will become the new Gods of Wall Street, and Darwinian Theory will kick in. The strongest will get a disproportionate amount of what’s on the table, whilst the weaker players will head downwards.
However, jumping on the bandwagon today for the fear of missing out it is wrong. There is a lot of peer pressure out there to make the leap and for many it will be painful. This is a highly complex and exciting style of computing, which costs $m’s, and require a left handed astronaut or two. If you don’t have these, then add in your job.
IBM claim only 1:10 IT teams have all the skills.
McKinsey Global Institute (MGI) forecasts a 50 to 60 percent gap between the supply and demand of people with deep analytical talent. Approximately 140,000 to 190,000 unfilled positions of data analytics experts in the U.S. by 2018 and a shortage of 1.5 million managers and analysts who have the ability to understand and make decisions using big data.
There is window of opportunity opening where the consumability of Big Data will become less risky and easier.
I am not the only one to advocate that “software = cloud”. Maybe not today, but software will = cloud. That is a FACT. This will drag the likes of analytics with it and with the exception of a very few elite players who have massively deep pockets, the majority of us will be leveraging cloud platforms to deliver our big data analytics. Platform as a Service (PaaS) is going to be an essential component in a Big Data strategy – watch the space.
As dotcom was a force of nature in the 90s, so Big Data is today. It is going to change many features in our landscape so respect it completely whilst embracing it.