Siebel书架系统。

简介：
Sophisticated analytical queries, mirroring those frequently employed in Siebel Analytics, meticulously examine substantial datasets utilizing intricate formulas. This examination can be considerably protracted when querying an Online Transaction Processing (OLTP) database, consequently affecting the overall efficiency of the system. Due to the protracted execution times of complex queries within OLTP databases, the data demands for Siebel Analytics diverge from those of other operational applications within the Siebel suite. While Siebel Analytics necessitates less frequent data modification compared to these operational applications, it simultaneously requires rapid results when exploring novel analyses, delving into detailed charts and graphs, and constructing fresh briefings. To satisfy these demanding needs, a tangible realization of the data model is crucial – one specifically optimized for swift review of the complete database’s information rather than for immediate updates. Such a database should incorporate as few join paths as possible to minimize computational workload. This translates to a reduced number of larger database tables instead of a multitude of smaller ones. Within this schema, identical data elements may appear across multiple locations, thereby diminishing the necessity for join paths. This particular database design is referred to as denormalized. The Siebel Data Warehouse functions as an online analytical processing (OLAP) database, empowering users to selectively extract, scrutinize, and visualize data. The structure of the Siebel Data Warehouse was deliberately crafted using star schema modeling techniques – often termed dimensional schema within this book – to effectively support the analytical requirements inherent in Siebel Analytics. To streamline this type of analysis, data from the Siebel Data Warehouse is stored within a relational database that treats each individual data attribute – encompassing elements such as product, account, and time period – as a discrete dimension. Importantly, the Siebel Data Warehouse does not encompass every single piece of data residing within a transactional database; only those elements pertinent to analysis are retained.