Much has been written about the need for metadata in ETL, Data Warehouse, and Business Intelligence environments. Business users need to know what their reports mean, where they came from, how reliable those reports are, and what other information is available. IT needs to know which sources are feeding data warehouses, how these sources are being transformed, who is accessing the BI reports and for what purpose, what load they are creating on the system, and more.

But is traditional metadata, added as an afterthought to warehouses and reports, sufficient to deliver real quality of information?
Can traditional metadata provide real agility as business vocabulary, rules, and underlying IT systems change?
Will traditional metadata support the need to directly tie business analysis from the BI environment to the operational systems?

In support of these goals, enterprises are now recognizing information management as an independent discipline which tracks information end-to-end - through the source systems, messages, to the data warehouse, to the data marts, and to the business reports. Specifically, they are adopting a semantic approach - Semantic Information Management (SIM) - to formally capture the business meaning of data at all stages of data production.

SIM is used to ensure that information is understood at all stages of this process, ultimately leading to consistent unambiguous business reports. SIM allows data translations to be automatically and accurately inferred. It provides the flexibility to respond instantly to changes in source systems, the warehouse schema, reports and the business vocabulary and business rules. Finally, SIM bridges the world of informational IT with the word of operational/transactional IT, making sure that source systems are understood and used consistently across all of IT in support of more flexible ways of doing business.