POS Applications, HR Applications, Customer Survey results; these are just some of the myriad sources of data that we are, as database administrators or developers responsible for - how do we store that data so that a Business Intelligence system can interrogate and provide meaningful results to the user.
Database Journal has the story on Business Intelligence: Your Data Storage.
"In practice, the terms data mart and data warehouse each tend to imply the presence of the other in some form. However, most writers using the term seem to agree that the design of a data mart tends to start from an analysis of user needs and that a data warehouse tends to start from an analysis of what data already exists and how it can be collected in such a way that the data can later be used. A data warehouse is a central aggregation of data (which can be distributed physically); a data mart is a data repository that may or may not derive from a data warehouse and that emphasizes ease of access and usability for a particular designed purpose. In general, a data warehouse tends to be a strategic but somewhat unfinished concept; a data mart tends to be tactical and aimed at meeting an immediate need.
"One writer, Marc Demarest, suggests combining the ideas into a Universal Data Architecture (UDA). In practice, many products and companies offering data warehouse services also tend to offer data mart capabilities or services.
"Other emerging technologies are being combined into new tools and software, which enables dynamic querying of real time data utilizing SOA to develop composable and adaptive middleware - there is a drive to name this type of BI as Business Intelligence 2.0. This renaming is has been attributed by Neil Raden as an attempt to imply a move away from standard storage systems (Data Warehouse and Data Mart) that current systems employ.