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How Will Business Analytics Change in the Near Future?

Here are seven changes ahead for enterprise analytics programs and practitioners– some of them expected sooner than later – as outlined by IIA’s CEO Jack Phillips and Director of Research Tom Davenport.

Widespread Business Culture Reliance on Data Widespread Business Culture Reliance on Data

Although the research on enterprise ROI from advanced analytics is sparse, those who have anecdotally found advantages are at the forefront of a change in how the organization sees the role of data, according to IIA. This is pushing analytics to a “watershed” moment where business culture expects analytics embedded into decision and operational processes, says Davenport.

Big Data is Just Part of Analytics Big Data is Just Part of Analytics

Davenport says that of the early adopters of enterprise big data, “not a single company” has a practice that separates big data efforts from other analytic practices. “Now is the time where, it’s not that the big data era is coming to an end, but it’s getting merged with traditional analytics.”

Move from Reporting to Prediction Move from Reporting to Prediction

At present, IIA states that 95 percent of analytic capabilities are based in either reporting or descriptive/visualizations. Among these other changes in the analytic landscape, IIA expects reporting to become more of an automated commodity, with approximately 90 percent of analytic capabilities shifted toward predictive and prescriptive practices.

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Analytic Teams Grow in Size, Importance Analytic Teams Grow in Size, Importance

Enterprise analytic leaders are already moving from the back office to the C-suite, but their roles and numbers will grow with the importance of data and the increase in trained, experience information managers. More IT leaders will assume the role of “Chief Analytics Officer” (though the title may be slightly different), and, with more business data interest and expectations, training will cross all business departments.

Data Warehouse Roles Lessen Data Warehouse Roles Lessen

While Davenport doesn’t see the data warehouse disappearing, he says it’s at least entering a new and less vital era in the enterprise. Hadoop and other data frameworks have led to “early stage data discovery that doesn’t necessarily involve a lot of ETL or time spent putting data in a warehouse without even knowing what the value of that data is.”

Honing in on Variety Honing in on Variety

Of the many definitions and “V’s” surrounding “big” data, the most important one as it relates to business capabilities will increasingly become variety. The size and storage challenges are minimal compared with the lack of structure and consistency with data, making variety the main target and obstacle in capturing real business insight.

Cashing in on Data Cashing in on Data

Certainly, trend-setting data purveyors, like Google and Facebook as well as digital advertisers, have been early entrants in this realm. But, with more sources of data and that data itself carrying more value, IIA states companies of all backgrounds will seek out ways to monetize this information, to varying degrees of success and scrutiny.

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Check out IIA’s “analytics 3.0” framework in greater detail here.
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If traditional reporting and decision support were at the start of modern analytics, and big data initiatives are at present, what’s the near future for analytics? The International Institute of Analytics outlined its new framework for what it calls “Analytics 3.0,” the future of making a business impact with varied and voluminous data.

 

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