Description: Metadata integration in data lakes refers to the process of combining metadata from various sources to create a unified view of the data assets stored in a data lake. Metadata is data that describes other data, providing information about its origin, format, structure, and context. This integration is crucial for the efficient management of large volumes of data, as it allows users to better understand the available information, facilitating its search, access, and analysis. By integrating metadata, data governance is improved, data quality is optimized, and interoperability between different systems and applications is enhanced. Furthermore, proper metadata integration helps organizations comply with privacy and security regulations by providing a clear framework on how data is handled and used. In environments where data lakes can contain structured, semi-structured, and unstructured data, metadata integration becomes an essential tool for organizing and leveraging these assets, enabling organizations to make informed decisions based on accurate and accessible data.
