Data lakes have become the norm in the industry for storing critical business data. The primary rationale for a data lake is to land all types of data, from raw data to preprocessed and postprocessed data, and may include both structured and unstructured data formats. Having a centralized data store for all types of data allows modern big data applications to load, transform, and process whatever type of data is needed. Benefits include storing data as is without the need to first structure or transform it. Most importantly, data lakes allow controlled access to data from many different types of analytics and machine learning (ML) processes in order to guide better decision-making.
Multiple vendors have created data lake architectures, including AWS Lake Formation. In addition, open-source solutions allow companies to access, load, and share data easily. One of the options for storing data in the AWS Cloud is Delta Lake.

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