Joe McKendrick

Throughout 2024, data managers and professionals were at the locus of the new waves of innovation driven by AI and analytics-and the activity was frenetic and intense. As the year 2025 progresses, this intense and frenetic activity will only continue. Cloud services, AI, AI agents, and cybersecurity are top areas of interest that industry leaders are watching. The following are several prominent trends mentioned that are shaping data management.

It has been a whirlwind time for data managers and their enterprises, and the innovations that are reshaping data operations aren't showing any signs of slowing down soon. AI and advanced analytics are changing the game, of course, as are a myriad of technologies now available to help manage and extract business value from the data flowing through organizations. Here is what industry experts tell BDQ they now see emerging and what we can expect in the months and years to come.

KDNuggets, a community site for data professionals, ranked 'We Don't Need Data Scientists, We Need Data Engineers,' by Mihail Eric, a venture capitalist, researcher, and educator, as its top story of 2021. This sentiment holds even more true today, especially with the unending rush to leverage both generative and predictive AI within enterprise operations. Without the right kind of data, AI is dead in the water.

Never before has the business spotlight been on database managers and professionals as it is at this time. Every business leader now wants a data-driven organization, as they recognize this is the key to competitive differentiation. Data monetization is seen as a vast new revenue source. AI-both operational and generative-relies on effective data management and quality. The ongoing transition to digital business demands real-time delivery of insights to end users and applications.

AI has become pervasive across enterprises, and the drive is now on to push this potentially powerful intelligence out to the edge and network, where it can deliver insight and operational performance in real time. These days, no discussion of edge and IoT is complete without weighing the implications of AI. ‘If people think AI will stop at data centers, they have an unfortunate blind spot, because AI is likely to be deployed in some form at the edge,’ said Kevin Brown, SVP at Schnei­der Electri…

Data management needs AI and machine learning (ML), and, just as important, AI/ML needs data management. As of now, the two are connected, with the path to suc­cessful AI 'intrinsically linked to modern data manage­ment practices,' said Dan Soceanu, senior product manager for AI and data management at SAS. Blazing this path requires 'pri­oritizing data quality, accessibility, and governance.'

AI-both operational and generative-is knocking on enterprises’ doors, forcing data managers to make new architectural choices on what it will take to support these data-hungry initiatives. Data mesh and data fabric are increasingly favored to help organizations get better control of their data, but which is the best option?

The momentous transformation putting data managers and their systems at the helm of modern enterprises has only begun. Industry leaders and experts agree that it’s critical for data managers and team leaders to design today’s data architectures to meet the demands of a digital economy, from cloud to real-time streaming to AI.

In the year ahead, data managers and their enterprises will be at a crossroads. Organizations will be leaning more heavily than ever on data-and the teams that manage it-for success with their customers, markets, and operations. The world of data is changing rapidly, and with it, its role in the business, from sitting on databases in the back end to competitive differentiation. Data is driving everything, everywhere.

It may be well-understood that cybersecurity needs to be front and center in all technology projects, but organizations are still slow or hesitant to fully commit to it. This is becoming a problem for data-intensive organizations, which need to brace for an onslaught of both external and internal threats. Only about one-half of organizations are beginning to recognize how important cybersecurity is from the start in any transformation effort, an Accenture survey of 3,000 executives shows.