The Rocket team is back and excited after from an incredible 360° experience at the Gartner Data & Analytics (D&A) Summit, March 3-5, in Orlando. With 5,000+ data, analytics, AI leaders, 200+ exhibitors from around the world, and game-changing discussions on AI, governance, and data strategy, the event was a deep dive into the current state of AI, data management, governance, and analytics and what the future holds for all of us.
We participated in the exhibition showcase, attended nearly every session, and even hosted one of our own. Michael Curry, President of Rocket’s Data Modernization business unit, world traveler, and sought-after speaker, gave a well-attended talk on Harnessing Mainframe Data for AI-driven Enterprise Analytics.
After experiencing the event from so many angles, we regrouped to compare notes. Some key takeaways stood out across the board.
While there are many valuable Data and Analytics-focused conferences worldwide (and more being announced almost daily), everyone agreed this is the “can’t miss” event for practitioners, thought leaders, and vendors alike. Though AI was the Summit’s theme, the sessions covered a wide range of topics, from driving business outcomes to enabling cultural change. Inspiration and impactful guidance abounded!
The conference underscored how overwhelming the rapid pace of change feels for data leaders. Where do I start? What’s best for my business—data mesh, data fabric, data lakehouse, AI? Some or all the above? While there are signposts, the “yellow brick road” has no single concrete direction. The guidance you’ll hear most often? “It depends.”
For most companies, focusing on a specific use case is the best starting point. Get your footing, iterate quickly, and learn as you go. Start small—clearly define your parameters, objectives, measurements, and internal capabilities, then jump in! Your first project may work out of the gate, or you may falter—the key is to learn quickly in a manageable way.
Michael Curry, VP of Data Modernization at Rocket, observed: “The level of investment in the data space continues to accelerate, now driven by AI, but the business cases and results from AI initiatives are still evolving. It’s critical to tie AI investments to business outcomes. The untapped/trapped data in the mainframes remain a major obstacle to building that strong business case.”
As AI accelerates the evolution of data management, it’s also reshaping the role of data and analytics professionals. While there’s still much ambiguity, and the pace of change can be overwhelming, it also presents golden opportunities to spotlight the importance of your role. Automating mundane, repeatable tasks like data cleaning, integration, and transformation frees you to focus on more strategic and analytical work, increasing your value by better supporting your company’s goals and ambitions.
For those of you lucky enough to be there, it was an amazing learning experience for everyone—and if you couldn't make it to this summit, we hope to see you at future Gartner events!
The Rocket Data Solutions team
Rocket® DataEdge™
Data integration solutions that prepare, access, manage, and interpret enterprise data to succeed in Hybrid Cloud.
Redefining the Role of AI and Mainframe Data in Enterprise Analytics
Data helps identify new revenue and business opportunities that would otherwise remain hidden.
Case Study: Large Financial Services Firm
Financial firm achieves metadata management success with Rocket DI.