At one time, when a business or IT person spoke of “business analytics,” they were talking primarily about reporting. Today, the reporting function would more likely be termed “business intelligence” Business analytics has evolved and expanded into an area that just five years ago was considered the exclusive domain of the technically esoteric; predictive analytics, or, the ability to take data and turn it into actionable information. Like airlines with their sophisticated yield management algorithms, businesses are trying to determine who will do what, when and for what price?
There are a number of trends beginning to surface on the predictive analytics front, and all promise to improve the way business is conducted. Some of the top trends include the following..
Until recently, big data consisted of disconnected bits of information from social networking, tweets, emails, RFIDs etc. wandering aimlessly through the ether. But now, the technology (Hadoop, for example) exists to gather and analyze this massive information bank. More and more, big data will become a cornerstone of predictive analytics.
Expansion of the user base
As predictive analysis tools become more user friendly, they will become a more accessible resource for business users. This will create the critical mass necessary to make predictive analytics a common practice, and will spur the continued development of new and better tools.
This goes hand in hand with item 2. Just as better software tools will expand user access to predictive analytics, the cloud will expand company access by eliminating the need for expensive infrastructure investment and maintenance. However, some are skeptical that the cloud will play a major role in the near term. Gartner, for example, predicts a penetration of just 3% of the market in 2013.
Everything is going mobile these days, including applications devoted to predictive analytics. Tools that aren’t mobile-enabled will fall behind, regardless of their effectiveness. As such, the push by software vendors to develop solutions that are enabled for mobile devices will continue at a rapid pace.
Support for Unstructured Data Analysis
oftware vendors today are providing solutions that can marry structured data with unstructured data. From a predictive analytics standpoint, this is a huge value add. By being able to include comments and notes, for example, a predictive model can contain much more complete and accurate data, and increase its accuracy.
These are five of the top trends in predictive analytics today, but in a field that is rapidly evolving and expanding, there is no guarantee that tomorrow won’t bring new technologies, new trends, and new opportunities. One thing is abundantly clear, however; the days of decision-making by crystal ball or simply looking backward are gone forever.