Metadata Warehouse is a database that contains the common metadata and client-friendly search routines to help people fully understand and utilize the data resource. It contains common metadata about the data resource in a single organization or an integrated data resource that crosses multiple disciplines and multiple jurisdictions. It contains a history of the data resource, what the data initially represented, and what they represent now.

A metadata warehouse is just like any data warehouse in that it stores all kinds of metadata to be used by the information system. Since today’s data driven business environments are relying heavily on data, there needs to be separate storage for both data and metadata in order for the enterprise data management system to function efficiently.

In the not so distant past, metadata has always been treated as a "second class citizen" in the database and data warehouse world. This may be because the primary purpose of a metadata is to define to the data. But with the evolution of information technology, the current emphasis on metadata in the world of data warehouses and software repository has elevated to new heights of prominence. Most business organizations now need metadata tool for efficient integration and change management.

When implemented and used properly, a metadata warehouse can provide the business organization with tremendous value so companies need to understand what metadata warehouse can and cannot do.

There are a lot of large business organizations nowadays that have had some experiences with data warehousing implementations. Today, data warehouses often take the form of data mart style implementations in many different departmental focus areas like financial analysis or customer focused systems that assist business units.

Many business enterprises have various initiatives related to data warehousing underway simultaneously and these systems are most likely based on products from various different data warehouse vendors in the typical decentralized approach of many companies. To date, the approach has mostly worked in that it has allowed reasonably rapid implementations and has shown companies that there are benefits to be derived and the potential of data warehousing being a business tool can be had at a fraction of the cost of the enterprise data warehouse model.

But this approach has got many companies to the legacy data Tower of Babel and some areas of the business have begun showing signs of stress in the implementation. Both data and metadata in this approach are spread across multiple data warehouse systems and the administrator are becoming stressed at coordinating and managing the dispersed metadata.

There need to be consistency in the business rules when they change as a result of corporate reorganizations, regulatory changes, or other changes in business practices. Likewise there should be a way to handle when an application wants to change the technical definition.

One of the significant steps to handle the needs stated above is coordinating metadata across multiple data warehouses and the way to achieve this is to have a metadata warehouse.

In an ideal corporate setting, a company should have adopted a repository as a metadata integration platform in order to make metadata available across the entire organizations. Doing this serves to manage the key metadata across al of the data warehouse and the data marts implementations within the business enterprise.

This can also allow all the data users to share common data structures, data definitions and business rules definitions from one system to another across the business organization. The metadata warehouse can efficiently facilitate consistency and maintainability as it provides a common understanding across warehouse efforts promoting sharing and reuse. This can result to better exchange of key information between business decision managers and reduced efforts in maintaining the information system as a whole.