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January 28, 2016

Gartner Sees Analytics Boom as More Data is Shared

Advanced analytics techniques like data and text mining, machine learning and visualization are poised to shake up entire industries as more enterprises leverage proprietary algorithms along with emerging platforms to securely share more data, a market watcher predicts.

In a forecast released Thursday (Jan. 28), Gartner Inc. predicted the red-hot advanced analytics market will grow 14 percent this year to $1.5 billion. By 2018, it predicts more than half of large global enterprises will leverage analytics and proprietary algorithms on secure platforms. The market watcher also sees a growing list of retail, financial and even professional sports applications as practitioners struggling to come up with big data strategies finally begin reaping a return on their investment.

“With fewer regulated monopolies and the Internet eliminating geographical boundaries, more companies are starting to use statistical analysis, predictive modeling and decision optimization to compete, instead of using traditional approaches,” noted Jim Hare, Gartner’s research director.

The key to gaining a competitive advantage will be accelerating the shift from “measurement” tools and “gut feel” decision making to predictive and other forms of advanced analytics. Gartner said such a shift might already be underway as more companies are focusing on developing proprietary algorithms for machine learning and other tools.

However, the trustworthiness of those analytics algorithms will remain an issue for most organizations even though factors influencing the “ethical use of analytics” are readily apparent, including transparency and accountability. “The resulting business, social and ethical impacts arising from the use of data and analytics are understood by few, ignored by many and tracked by virtually no one,” added Gartner analyst Alan Duncan.

The market watcher also predicts that an emerging analytics algorithm marketplace will be combined with platform-as-a-service (PaaS) offerings by 2018. If that prediction holds up, it could boost the sharing of “detailed, event-driven data,” Gartner concludes. Licensing, data integration and trust issues have so far hindered greater sharing of such high-value data.

“The solution will be the combination of algorithm marketplaces and PaaS-runtime environments, where only specifically certified functions are allowed to process the secured data,” the market watcher observed. The combination will help spread the use of advanced analytics by enabling secure sharing that promises to monetize more unstructured and other raw data.

Within the next several years, Gartner analysts said they expect new analytics and IT technologies to merge “that can radically simplify the trust, licensing and data integration challenges, by placing controls on the algorithmic data processing.” With those tools in place, “Only certified components will be able to run sensitive data and transform it into scoring and optimization models,” Gartner added.

That means data processing would be constrained to ensure underlying, detailed data cannot be copied.

Along with data mining, machine learning and visualization, Gartner also forecasts greater uptake of emerging analytics technologies like semantic and graph analyses, simulation, complex event processing and neural networks.