Metadata and Data Warehouse Quality

摘要: In the traditional view, data warehouses provide large-scale caches of historic data. They sit between information sources gained externally or through online transaction processing systems (OLTP), and decision support mining queries following vision analytic (OLAP). Three main arguments have been put forward in favor this caching approach: 1. Performance safety considerations: The concurrency control methods most DBMS do not react well to a mix short update transactions (as OLTP) OLAP that typically search large portion database. Moreover, OLTP are often critical for operation organization must be danger corruption by other applications. 2. Logical interpretability problems: Inspired success spreadsheet techniques, users tend think terms highly structured multidimensional models, whereas offer at best relational, just semi-structured models. 3. Temporal granularity mismatch: focus on current operational great detail, considers historical developments somewhat less detailed granularity.