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Converged, Cloudy and Cognitive: The Top Information Management Trends for 2021

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There are other advantages seen in these next-generation platforms as well. “Aside from savings in hard costs, busi­nesses should benefit from the machine learning capabilities built into many PaaS platforms that have capabilities of self-healing and self-managing,” Caruso said. “PaaS solutions reduce the adminis­trative burden on some technical staff, like database administrators, allowing them to shift their focus to more value-added activities. Businesses also benefit from engineered capabilities like high availabil­ity, automated disaster recovery, and auto­mated scalability to account for seasonal peaks in utilization.”

Data Management Automation 

The year ahead will also see a greater push toward the automation of data man­agement functions. “Data preparation tools were the first to adopt automation in the form of data standardization, de-du­plication, and parsing,” said Todd Wright, head of data management solutions at SAS. “With machine learning techniques, these manual tasks can be performed by the software either by offering up sugges­tions for data corrections or performing the corrections on its own.” For the year ahead, he said, expect to see greater auto­mation “in the areas of data cataloging, metadata management, reference data management, and data glossaries.”

At this point, he continued, “data man­agement automation is bubbling under thesurface. However, many organizations are beginning to understand that the current way of performing data management is not sustainable and are realizing from a resource and time perspective that automation of routine tasks must become a reality.”

Hyperautomation 

As Wright explained, automation promises to make data managers’ work lives more manageable and productive. At the same time, we may be entering an era of what Ed Macosky, head of product for Boomi, a Dell Technologies Business, calls “hyperautomation.” Hyperautoma­tion, driven by AI, “will help businesses categorize the data and draw new, action­able insights from it,” he explained. “What AI and hyperautomation will do for data in the next year exemplifies that merging of IT and business. Hyperautomation bridges the gap between the influx of data and demand, and companies’ limited bandwidth.”

AI-Driven Processes

Augmented processes—made possi­ble through robotic process automation (RPA) and AI—will increasingly be seen as the route to competitive advantage. “To truly have an intelligent business involves so much more than simply collecting data and getting insights,” said Ana Maloberti, subject matter expert for big data at Glo­bant. “Stop thinking of data as an after­thought to be exploited for insights and embrace it as part of a bigger strategy for deeper understanding, process optimiza­tion, and innovation.”

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