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.
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The past year saw AI go from a pipe dream to a reality. Businesses are rushing to do what they can to integrate automation into their systems and offer their own AI technology, leading to increased security, tapping into the cloud, and more. As 2024 begins, DBTA presents the annual MultiValue Special Report and asks MV executives to address several questions.
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According to Gartner's Hype Cycle for Emerging Technologies, generative AI (GenAI) has reached the "Peak of Inflated Expectations." What does this mean in simple terms? Essentially, right now people's expectations of what the technology can do doesn't align with reality. As such, companies can make costly mistakes if they let hype or FOMO lead their GenAI strategy and investment. That said, even as GenAI is generating a lot of hype, it can also generate tremendous value if businesses do it right.
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Public cloud has skyrocketed to become the indisputable go-to destination for new IT workloads, especially for data. And while the cloud is full of advantages over on-premises data platforms, cost optimization rarely makes that list. Since modern data professionals' roles encompass building and maintaining this platform, they should also be aware of how to objectively reduce the data platform costs to eliminate this enormous, missed business opportunity.
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