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Real-time data analytics aims to boost businesses' speed of thought

Real-time business intelligence can help improve operational decisions by enabling BI to be done in business systems. Read about how to make it work.

In an interview published on TechTarget's ebizQ website in 2011, Gartner analyst Roy Schulte discussed efforts by a growing number of the consulting company's clients to make their business systems "smarter" through the addition of integrated analytics capabilities. One of the driving forces Schulte cited was a desire to improve decision making -- on the fly -- by undoing the usual decoupling of business intelligence and advanced analytics systems from business applications. "There's a gap between what the business intelligence department knows and what the people running the business know," he said in the interview.

Schulte still sees lots of value in closing that gap: Interviewed again for a recent series of stories on real-time data analytics, he told contributor Beth Stackpole that every company has operational processes requiring immediate decisions, and that having access to real-time business intelligence (BI) and analytics data can help business users make more effective decisions in such situations.

Real-time -- or, more commonly, near-real-time -- analytics is particularly popular with Wall Street trading firms and managers of corporate call centers. But it also has uses in transportation, health care and other industries. If your organization is looking to go down the real-time analysis road, you'll find practical advice on evaluating, planning and managing deployments in our series. In one story, we examine the business case for real-time analytics. We also look at the benefits and challenges of combining big data and real-time BI systems. And we detail real-time data analysis best practices -- as well as some steps that are best to avoid in real-time rollouts.

Craig Stedman is executive editor of Email him at, and follow us on Twitter: @BizAnalytics_TT.

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