Put Big Data Playtime to Bed

If you’re an on-the-job analytics professional, you may feel the pressure starting to build. Big data playtime is over, and real work needs to get done — now.

It’s a bit of a “big data shakeout,” in the words of Sarah Gates, vice president of research at the International Institute for Analytics (IIA). I talked with Gates last month following the IIA’s formal unveiling of its 9 Analytics Predictions for 2014.

From what the IIA sees of its clients, organizations are starting to align big data and business problems more aggressively, Gates told me. They’re outfitted with advanced analytics applications and plenty of compute power, and they want positive business outcomes. “They’ve moved big data out of the hype phase and are settling down to solving business problems with new tools and new sets of data.”

This determination to reap value from big data, of course, has all sorts of ripple effects, as we learned in the IIA’s other nine predictions. Gates was most taken with the notion that companies will increasingly use data analytics to create products and services. “That’s absolutely cool in that it’s about opening up new competitive areas using data and analytics, and looking at things completely differently.”

It’s a favorite trend of hers, as an analyst and as a consumer. “There are products and services I never knew I wanted or needed or would be able to get that are now available.” She cited not only popular uses of big data analytics like Amazon’s book recommendations and LinkedIn’s people matching, but also “things that are much more practical in terms of their impact on agriculture, safety, and equipment.”

Should two of the IIA’s other predictions come to fruition, the result would have far bigger impact. These are the predictions dealing with the continued move toward machine learning and automated construction of models — to keep up with the speed and volume of the data — and with embedding those models into business processes. “So many organizations have yet to take advantage of embedding models into their operational processes and helping to automate or improve the decision making that happens in every part of their businesses. But that has such incredible potential for so many types of business across industries in 2014.”

However, even absent full automation, having decision support inserted into a business process brings a host of technology and organizational implications, Gates said. Naturally, these implications make the people challenge as large as ever. The IIA sees the analytics talent issue manifesting itself this year via a shift in focus from individual analytics professionals to analytics teams. But companies still have to find, nurture, and retain the talent, even if it may find itself embedded in the business organization or networked in a community or center of excellence.

Gates expounded on that topic during a video interview we shot at last fall’s Analytics 2013 conference hosted by our site sponsor, SAS. She’s got great advice to share on how to recruit and leverage analytics talent, whether your organization is big or small. Check it out.

I’m sure the bulk of companies will continue to grapple with big data (talent and technology wise), while those at the leading edge will encourage everyone with their cool success stories. We’ll be here to share it all — the good and the bad. We hope you share with us, as well.


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