AI, Automation, and New Ways of Getting More Value From Data

As restrictions caused by the pandemic begin to ease and a “new normal” for business comes into view, some organizations are emerging as winners. Key to thriving and not just surviving, many experts say, is the ability to use data more effectively, enabled by the well-applied use of the right database technologies and cloud resources as well as automation and AI.

The implications of these transformative technologies are examined from a range of perspectives in a variety of articles in the Summer issue of Big Data Quarterly magazine.

In his cover article exploring current database management trends, our contributing editor Joe McKendrick notes that if there is one characteristic that singularly dominates the data scene now, it is the vast assortment of systems available. Today, he points out, there is a database for every type of function, creating choice and opportunity but also requiring knowledge about the best database environment for the use case.

DataOps, MLOps, robotic process automation, and low-code/no-code development are some of the new approaches taking hold, according to Radiant Advisors’ John O’Brien, who shares his take on the top technology trends helping organizations gain value from their data. There is a new appreciation for being agile in terms of BI and data analytics since, over the course of the past 15 months, many companies have discovered that what they were doing was simply not fast enough, O’Brien notes. DataOps is building on the best practices that have emerged from the DevOps world and is relying heavily on automation and data governance, adds Zaloni’s Ben Sharma in a separate interview. “You must be able to use data effectively in a timely manner so that you can adapt to change,” Sharma stresses.

Adding to the discussion of where AI and automation can add value, NVIDIA’s Jim Scott shares how natural language processing methods are now being used to automate the task of parsing network security logs.

A number of authors in this issue also focus on the human considerations involved in new technology adoption. LicenseFortress’ Michael Corey and VMware’s Don Sullivan weigh in on the impact of what they call the coming “tsunami of automation.” As companies increasingly look to automation to address the intertwined concerns of labor availability, profitability, efficiency, and speed, there is almost nothing outside of the arts and sports that will not be automated, they suggest. Also looking at automation and innovation from the human perspective, Software AG’s Bart Schouw relates his own experience as a consumer purchasing a high-end “smart” oven and the problem of achieving the critical last mile of customer service. Connected products necessitate connected CX across all channels, he concludes. Meanwhile, Veeam’s Danny Allan considers what’s necessary to achieve the productivity that DevOps promises and observes that cultural shifts are the hardest kinds of reorganizations to pull off.

And there are many other articles that examine the use of new approaches and best practices to improve data analytics, security, and governance. Radiant Advisors’ Lindy Ryan spotlights the challenges of data-enabling the entire organization, SAS’ Kimberly Nevala looks at AI governance, and EPAM Systems’ Sam Rehman underscores the importance of embedding security by design to defend the enterprise against cyberthreats.

The Summer 2021 issue of Big Data Quarterly also features a special report on "Data
Strategies for the Real-Time Era."

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