Why is metadata critical for managing large datasets?

Explanation: Metadata acts as a blueprint for understanding datasets, enabling efficient organization, discovery, and compliance. For instance, metadata in a data lake catalogs files by attributes like creation date, author, or format, making data retrieval seamless. Metadata also ensures governance by tracking data lineage, maintaining data integrity, and complying with regulatory standards. This is especially vital in Big Data environments where datasets are diverse and voluminous. Effective metadata management streamlines data processing, making analytics more robust and actionable. Option A: Metadata does not reduce dataset size; it complements the data by providing descriptive information. Option B: Metadata does not directly influence model accuracy, though it aids in data preparation. Option D: Metadata does not replace data cleaning but supports better data management. Option E: Metadata helps locate and organize data but does not inherently speed up query processing.