Data Lake

A data lake is a large-scale storage repository and processing system. It can store both structured and unstructured data in its raw format until it's needed. The primary purpose of a data lake is to offer an unmodified, granular, detailed level of data to scientists, analysts, and other users to assist with their analysis and reporting.

The concept of a data lake is closely related to big data. In a data lake, data does not need to be pre-structured or cleansed before it's stored. Users can explore the raw data as needed, applying any transformations and cleaning processes as required for their purposes. This approach is different from a traditional data warehouse, which transforms and cleanses data before storing it.

Data lakes are generally associated with Hadoop-oriented technologies, but they can also be implemented using other technologies as well. They are particularly useful for machine learning, real-time analytics, and big data scenarios.

The metaphor of a lake is used to illustrate the idea that information from various sources flows into the data lake, creating a large body of raw data in its natural state. The information can then be analyzed directly, or it can be extracted and transformed for more specific purposes.

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