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2014: Predictive Analytics Tools to the Rescue

The big data predictions for 2014 are coming in, and it appears the focus next year will increasingly be on analytics. Throughout 2013, much ink (and many pixels) were dedicated to talking about the dearth of data scientists. Colleges and universities have been scrambling to roll out programs to train people to work in this growing field. But the prospect of trained data scientists emerging from these programs, ready to join the workforce, is still several years out.

However, there is an easier and more immediate solution to the problem at hand. As Roger Barga, group program manager for Microsoft’s Azure Data Platform, noted at the Microsoft Faculty Research Summit in Redmond back in July, a quicker solution to the problem might be developing analytics applications that enable those without high-level data analysis skills to make sense from large streams of unstructured data. Such applications would also enable the highly trained to come up with results more efficiently.

Greg Todd, chief technology officer at predictive analytics platform provider Revolution Analytics said in a recent ZDnet post that analyzing large data sets to understand customer behavior used to be the province of statisticians and management scientists. However, with the emergence of predictive analytics communities, vendor applications are becoming more "visual, easier to use, and geared more towards business analysts vs. the hard-to-find statisticians and management scientists of the world."

Steven Hillion, Chief Product Officer at web analytics platform Alpine Data Labs, also foresees increasing emphasis on collaborative and web-based solutions for data science and advanced analytics. Furthermore, he expects that machines will eventually take over decision-making based on analytics.

Most are in agreement that 2014 will see a burst of new and better analytics tools to join those already being used. And spending less time collecting and analyzing information will have the powerful result of leaving more time for acting on it and understanding it, says Radhika Subramanian, CEO of pattern-discovery provider Emcien

Activity in the big data world is frenetic. Industry verticals are still learning how to leverage its power. Investors are supporting increasing numbers of new startups. Established solutions providers are rushing to improve their products and introduce new ones. And enterprises are struggling with which solutions to use.

The lack of trained data scientists has the potential to slow down progress in the entire ecosystem. However, if predictive analytics platforms and tools can be designed to be used and understood by business analysts, that would certainly help the industry overall.

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