Skip to main content

Short note: Data marts and metadata

Short answer

Data marts are subject-specific subsets of a data warehouse, built for one department; they are cheaper and faster. Metadata is data about the data, including technical (source mappings, schema), business (definitions), and operational (load history) descriptions to help users understand and maintain the warehouse.

Write a short note on Data Marts and Metadata in DW.

Data mart

A data mart is a subset of the data warehouse designed for one department or subject (sales, finance, marketing). It holds less data, is cheaper and quicker to build, and gives faster response. Types: dependent (fed from the enterprise warehouse), independent (fed directly from sources) and hybrid. Example: a Marketing mart holding only customer and campaign data.

Metadata

Metadata is "data about data". It describes the warehouse contents and how they were created. Types:

  • Technical (back-room) metadata: source-to-target mappings, schema, transformation rules, load schedule, data lineage.
  • Business (front-room) metadata: business terms, definitions, ownership, report descriptions, so users can understand the data.
  • Operational metadata: load history, data currency, usage statistics.

It is used by ETL tools, the warehouse and query managers, and end users; without metadata, the warehouse is hard to use or maintain. Example: metadata for column amt says: "sales amount in NPR, from POS table BILL.TOTAL, loaded daily at 11 pm".

✓ Answer checked by Claude Opus 5.5 (high effort)

Related questions

All Data Mining chapter 1 questions →