Organizations often gather enormous amounts of data and continue to produce ever-increasing amounts of data, ranging from terabytes to petabytes and occasionally even exabytes. Such data is typically produced by various systems and needs to be gathered in one place for analysis and insight creation. You may combine data from several silos, store it in a single location, impose data governance, and support analytics and machine learning (ML) on top of this data by using a data lake architecture.


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Special Thanks to Authors where i was able to learn and implement my own versions using serverless framework

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