The Top Information Management Trends For 2023

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In the year ahead, expect to see increasing emphasis on edge and Internet of Th­ings computing, particularly as 5G gains ground as a way to rapidly acquire and process data.

McKinsey predicts that as a result of 5G proliferation, edge will be the hotbed of innovation in the year ahead. “5G will deliver network speeds that are about ten times faster than current speeds on 4G LTE networks, with expectations of speeds that are up to 100 times faster with 40 times faster latency,” the consultancy stated.

­This will boost development of real time applications such as AI-driven speech, written word, or computer vision algorithms. “­There are lots of emerging database technologies that can help IT managers and developers—especially with next-generation distributed applications, such as those powered by the telco cloud, 5G, and now, 6G,” said Jason Carolan, CIO of Flexential.

“Data coherency and eventual consistency is becoming better understood, and many smaller startups and even the bigger database players are increasing their offerings in the distributed and cloud database markets. This will help us develop new IoT applications and make better, more efficient data-driven locations for smart cities, manufacturing, healthcare, and beyond.”


­The year ahead will witness more active efforts to deploy data in new ways that open up new lines of business for enterprises. “Today’s business leaders see the inherent value in data monetization, an opportunity spurred by the emergence of data marketplaces and the ability to access both internal and external data,” said Helena Schwenk, vice president and chief data and analytics officer for Exasol. However, data won’t automatically sell itself, she cautioned. New data products will need to be carefully designed and managed by data teams—with the help of enhanced automation. “In many cases, there is a large opportunity to optimize the setups, systems, processes, and communication needed to turn an idea into a data product that can be leveraged to make better decisions. All solutions that automate parts of that process support this vision.” Automating the data-to-value process “will help improve time efficiencies for data pipelines, instantiation of data platforms, and ultimately improve data accessibility. ­This way, organizations can gain commonality within their data architecture and access better insights to support and optimize operations.”

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