Meta Data Repository:
Metadata is data about data. When used in a data warehouse, metadata are the data that define warehouse objects. Metadata is created for the data names and definitions of the given warehouse. Additional metadata are created and captured for timestamping any extracted data, the source of the extracted data, and missing fields that have been added by data cleaning or integration processes.
A metadata repository should contain the following:
A description of the structure of the data warehouse, which includes the warehouse schema, view, dimensions, hierarchies, and derived data definitions, as well as data mart locations and contents.
Operational metadata, which includes data lineage (history of migrated data and the sequence of transformations applied to it), the currency of data (active, archived, or purged), and monitoring information (warehouse usage statistics, error reports, and audit trails).
The algorithms used for summarization, include measure and dimension definition algorithms, data on granularity, partitions, subject areas, aggregation, summarization, and predefined queries and reports.
The mapping from the operational environment to the data warehouse includes source databases and their contents, gateway descriptions, data partitions, data extraction, cleaning, transformation rules, and defaults, data refresh and purging rules, and security (user authorization and access control).
Data related to system performance, which include indices and profiles that improve data access and retrieval performance, in addition to rules for the timing and scheduling of refresh, update, and replication cycles.
Business metadata, which includes business terms and definitions, data ownership information, and charging policies.