Liran Zvibel, Cofounder & CEO, WEKA. Read Liran Zvibel's full executive profile here.
Artificial intelligence. Machine learning. Quantum computing. Technologies that were once the stuff of science fiction are now shaping a new era of intelligent innovation, evolving faster than anyone could have imagined.
One key reason is that the legacy data architectures and data management approaches that previously governed enterprise technology stacks were conceived and constructed long before the emergence of the cloud and AI era. In the wake of accelerated compute and a new breed of performance-intensive workloads, the approaches we’ve relied on for decades are rapidly devolving.
Instead of aggregating data and metadata into large, static datasets confined within storage silos, data liquidity breaks down information into countless tiny shards. These shards can then be efficiently distributed across computing cores and storage resources, facilitating the unrestricted flow of data to the precise resources that require it.
Fast forward to 2023, when generative AI exploded on the scene. Traditional data architectures and data storage approaches can no longer accommodate the scale, velocity and data flow requirements of AI workloads, necessitating a new data framework for the future. A data platform approach has never been more critical.Although data platforms provide a strong foundation to help solve scalability, performance and data accessibility challenges, they can give way to other issues.
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