Real-time analytics seen as key for successful data management strategies

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Operating as a digital business means being fast—whether it’s responding to customer queries, getting products and services out the door, or reacting to a change in the market. Real-time analytics plays into this need for speed, and has become a key component of data management strategies.

More companies are looking to perform analytics on data as soon as it comes into systems and applications, in order to gain insights more quickly. This could include analyzing data about customer transactions, Web site navigations, social media interactions or any other type of activity.

In a February 2019 report in which it identified the top 10 data and analytics technology trends for 2019, research firm Gartner Inc. said by 2022 more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.

Continuous intelligence, listed as one of the top trends, is a design pattern in which real-time analytics is integrated within a business operation, the firm said. It processes current and historical data to prescribe actions in response to events, and provides decision automation or decision support.

Continuous intelligence is enabled by technologies such as augmented analytics, event stream processing, optimization, business rule management and machine learning, Gartner said.

It represents “a major change in the job of the data and analytics team,” said Rita Sallam, research vice president at Gartner.

“It’s a grand challenge—and a grand opportunity—for analytics and BI [business intelligence] teams to help businesses make smarter real-time decisions in 2019,” Sallam said.

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