Rise Of The Data Platform, Part Two: Real-World Considerations For Building An AI-Ready Enterprise Data Stack

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Rise Of The Data Platform, Part Two: Real-World Considerations For Building An AI-Ready Enterprise Data Stack
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Liran Zvibel, Cofounder & CEO, WEKA. Read Liran Zvibel's full executive profile here.

and how a modern data platform approach can be a key component in this evolution. But in a world where next-generation technologies and workloads like generative AI , machine learning , quantum computing and ever more dense GPUs are rapidly evolving, how can you be sure you’re building a data architecture that can keep pace with future innovation? As usual, the devil is in the details.

As you evaluate data platforms or other types of data infrastructure solutions, I strongly recommend making sure they can grow with you into the future. They should be able to run in your on-premises environment and extend natively into the cloud or clouds of your choice, providing a consistent experience across all the environments you need to connect to.

Done right, this approach should help deliver a multidimensional value proposition of speed, scale, simplicity, sustainability, savings, security, safety, and software, or what I call the eight S’s, which coalesce like a symphony to create perfect harmony in your data environment.

Whatever you choose, one thing is clear: Data is fueling innovation at a breakneck pace, and ensuring readiness can help fully maximize its value.

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