What is a data lake?

A data lake is best described as a large storage system that holds vast amounts of raw data in its native format. This means that it can accommodate various types of data, including structured, semi-structured, and unstructured data, without the need for prior processing or transformation. The flexibility of a data lake allows organizations to store data in its original form, making it accessible for different analytics and processing tasks later on. This contrasts with traditional data storage methods, such as data warehouses, where data is usually cleaned, transformed, and structured before storage.

In a data lake, the raw data can be stored until it is needed for analytics, machine learning, or other processes, thereby supporting a wide variety of use cases. This approach enables organizations to leverage data from multiple sources and different types of data, empowering them to extract insights and derive value from their data assets over time.