What is metadata?
Metadata is data about data, information that describes a dataset's structure, meaning, origin and context rather than its actual values. Examples include table and column names, data types, descriptions, creation dates, ownership and lineage. It helps people and tools find, understand and trust data.
If a table is the data, metadata is everything that tells you what that table is: its schema, the meaning of each column, who owns it, where it came from, when it was last updated, and how it relates to other data.
Metadata is often grouped as:
- Technical table and column names, types, keys, indexes.
- Business plain-language definitions and ownership.
- Operational freshness, load history, lineage.
Rich metadata is what makes data discoverable and trustworthy; missing metadata is why so many databases feel like a maze of cryptic column names.
iDBQuery both reads and enriches metadata. During introspection it captures the technical metadata of every source, tables, columns, types and relationships, and its semantic layer adds a business layer on top, learning what obscure fields actually mean and how they connect. That is why you can ask a plain-language question against a schema you have never seen and get a correct, cited answer: iDBQuery has already understood the metadata for you. It effectively builds a living data dictionary as a by-product of connecting your sources.
Updated 2026-06-22