Data Warehouse metadata
The metadata in a data warehouse system unfolds the definitions, meaning, origin and rules of the data used in a Data Warehouse. There are two main types of metadata in a data warehouse system: business metadata and technical metadata. Those two types illustrate both business and technical point of view on the data.
The Data Warehouse Metadata is usually stored in a Metadata Repository which is accessible by a wide range of users.
Business metadata (datawarehouse metadata, front room metadata, operational metadata) - this type of metadata stores business definitions of the data, it contains high-level definitions of all fields present in the data warehouse, information about cubes, aggregates, datamarts.
Business metadata is mainly addressed to and used by the data warehouse users, report authors (for ad-hoc querying), cubes creators, data managers, testers, analysts.
Typically, the following information needs to be provided to describe business metadata:
Technical metadata (ETL process metadata, back room metadata, transformation metadata) is a representation of the ETL process. It stores data mapping and transformations from source systems to the data warehouse and is mostly used by datawarehouse developers, specialists and ETL modellers.
Most commercial ETL applications provide a metadata repository with an integrated metadata management system to manage the ETL process definition.
The definition of technical metadata is usually more complex than the business metadata and it sometimes involves multiple dependencies.
The technical metadata can be structured in the following way:
Some tools dedicated to the metadata management(many of them are bundled with ETL tools):