Data platforms in the cloud have come a long way from their origin point, and continue to evolve.
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Traditionally, a data warehouse has sat at the heart of analytics, absorbing data from different business systems to support business intelligence.
However, that was a fairly limited and expensive set-up, requiring a defined schema before loading data and with high capex and opex costs.
That approach later evolved into a data lake, but it had similar limitations in terms of high costs, limited capacity scaling and the need for in-house experts.
In the video below, Rajan discusses analytics moving from on-prem set-ups to the cloud; the responsibility that comes with doing so; and the way that these systems have continued to evolve into intelligent data platforms - and, soon, the addition of generative AI.