I was invited to a Gartner Analyst Day last week. As youd expect from Gartner, it was chock full of high quality material. The theme, hunting and harvesting business performance in a digital world, was organized around a few flagship topics - Big Data & Analytics, Bring Your Own Device, Security and Business-Outcome Based Service Levels. The presentation that hit home for me was Big Data & Analytics. Anne Lapkin, a Gartner Research VP, spoke to couple of compelling points.
In the Gartner view, somewhere around 2009, multiple computing technology advances converged to open the door to big data as a mainstream information technology. CPU, memory, networking and database technology all made step changes. Together these advances laid the foundation for big data to become a pervasive business technology. By 2015, the hype about big data will be over and the concepts will become threaded into the business of IT. By 2020, we will no longer have a concept of big data because it will be completely woven into the fabric of the business computing. It will be the price of admission.
Big data is just lots of data. Some industries have been dealing with big data for a long time. The oil and gas industry, for example, has been processing big data for decades as a critical element of finding and producing petroleum. This is a newer phenomenon in other industries like the power distribution industry with Smart Meters. One of the big drivers behind the growth of big data is the internet of things. Gartner predicts that by 2020, we will have 31 billion connected devices generating data at very high volumes, velocity and variety. The ratio of spending today between skills and software licenses is 20:1. A strong shift toward license spend will signal that the technology is being adopted into the mainstream.
Analytics is about decision making. Its both a major opportunity and an essential technique for dealing with very large volumes of data. The evolution of analytics can be characterized as a progression through a sequence of decision types. The evolution begins at Diagnostics (whats happened?), moves to Description (why did it happen?) then to Prediction (whats likely to happen?) and finally to Prescription (what should I do next?). Today, mainstream analytics has evolved to Diagnostics and Description with structured data types. The next big step is into Predictive analytics using hybrid data a mix of structured and unstructured data types.
If you are interested in Big Data, join the next World Financial Symposiums Market Spotlight webcast on March 26, sponsored by Corum.