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BigLake with Gaurav Saxena and Justin Levandoski

Google Cloud Platform Podcast

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Big Data Warehouses - What's the Value Gap?

12 years ago, if you look at how analytics was done, it was primarily about a move all date together in data warehouse and enable sequel workers on top of i think what happened was that when data volumes became large enough, harop really paved the way for large scale data processing. And object stores matured to become data lakes. But they have typically lacked the features that data warehouses provided - things like finerand security perform incuary execution transactions. This is one of the reasons why you are seeing a lot of interests in market around big lake because it is exactly the problem that we are set out to solve.

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