What is one characteristic of raw data stored in a data lake?

Raw data stored in a data lake is characterized by the fact that it is not subject to predefined schemas. This is essential to the nature and utility of data lakes, which are designed to handle large volumes of data in various formats—structured, semi-structured, and unstructured—without the need for a fixed schema. This flexibility allows organizations to store data as it is, providing the opportunity for later exploration, analysis, and transformation as needed.

This characteristic enables data lakes to easily accommodate diverse data types from different sources, making it a versatile choice for analytical tasks. The lack of a predefined structure means that users can ingest data quickly and in its raw form, allowing for agile data science processes and enabling insights that might not be possible with traditional database systems that require structured data upfront.