Metadata in databases: Which activity is not enabled by reviewing metadata supplied by the DBMS or data catalog?

Introduction / Context:Metadata is “data about data.” In databases, metadata includes table and column definitions, data types, constraints, keys, relationships, descriptions, and sometimes lineage information. Analysts and engineers rely on metadata to understand and govern data assets without directly scanning all row values.

Given Data / Assumptions:

• Metadata describes structure, meaning, and rules, not necessarily the actual row contents.
• Catalogs, information_schema views, and data dictionaries expose metadata.
• Sampling row data requires reading the data itself, not just metadata.

Concept / Approach:Use metadata to discover what entities exist, how they relate, what constraints apply, and what each field is intended to represent. When you need examples or distributions of values, you must query the actual tables or use profiling tools that read data, which goes beyond pure metadata.

Step-by-Step Solution:

Verification / Alternative check:Check any RDBMS system catalogs: they describe schema but do not contain representative row samples unless a profiling feature separately stores them.

Why Other Options Are Wrong:

• Understand what data exist: metadata lists tables, columns, and objects.
• Fine distinctions and meanings: documented descriptions, enums, and constraints help explain semantics.
• Identify structures and relationships: keys and foreign keys are part of metadata.

Common Pitfalls:Assuming a data catalog includes data previews by default. Some tools offer previews, but that is a convenience feature that reads data, not metadata itself.

Final Answer:Sample data.