Data Summit 2026 is rapidly approaching on May 6 - 7 in Boston, with pre-conference workshops on May 5, delivering a high-impact learning experience for data and AI professionals at every level. Attendees will gain practical strategies and forward-looking perspectives from industry leaders who are addressing the challenges and opportunities shaping the future of data. DBTA recently spoke to John O'Brien, program chair for the event and principal advisor, industry analyst at Radiant Advisors, about what to expect at this year's event.
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Artificial agents, applications, and bots are popping up across every enterprise landscape, and data is rolling through at a fast and furious pace. While there has been plenty of hype, excitement, and fear about AI's possibilities, there has been scant attention regarding the data infrastructure needed to make it all work—especially at the enterprise level. AI requires a strong and well-considered data foundation, whether it's extended out of legacy infrastructures or part of the next generation of data technology.
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When organizations think about green IT, they usually consider data center efficiency, server consolidation, or cloud energy metrics. And yes, those are important areas, but they overlook one of the biggest contributors to an organization's energy footprint: its data architecture. Every table, index, column, backup, replication stream, and query consumes resources, and therefore energy. Poor data design doesn't just slow performance or inflate costs, it also increases the organization's environmental footprint.
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Flash pricing is rising, but cost is no longer the only variable storage leaders must consider. Reliability, availability, and continuity of supply are now central to infrastructure planning. A large share of global flash manufacturing remains geographically concentrated—meaning even temporary disruptions could quickly affect pricing, lead times, and an organization's ability to execute storage and AI initiatives on schedule.
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