Databases and database theory have been around for a long time. Early renditions of databases centered around a single database serving every purpose known to the information processing community—from transaction to batch processing to analytical processing. In most cases, the primary focus of the early database systems was operational—usually transactional—processing. In recent years, a more sophisticated notion of the database has emerged—one that serves operational needs and another that serves informational or analytical needs. To some extent, this more enlightened notion of the database is due to the advent of PCs, 4GL technology, and the empowerment of the end user.
The split of operational and informational databases occurs for many reasons:
The data serving operational needs is physically different data from that serving informational or analytic needs.
The supporting technology for operational processing is fundamentally different from the technology used to support informational or analytical needs.
The user community for operational data is different from the one served by informational or analytical data.
The processing characteristics for the operational environment and the informational environment are fundamentally different.
Because of these reasons (and many more), the modern way to build systems is to separate the operational from the informational or analytical processing and data.
This book is about the analytical [or the decision support ...