文档介绍：DATA WAREHOUSE
Data warehousing provides architectures and tools for business executives to anize, understand, and use their data to make strategic decisions. A large number anizations have found that data warehouse systems are valuable tools in today'petitive, fast evolving world. In the last several years, many firms have spent millions of dollars in building enterprise-wide data warehouses. Many people feel that petition mounting in every industry, data warehousing is the latest must-have marketing weapon —— a way to keep customers by learning more about their needs.
“So", you may ask, full of intrigue, “what exactly is a data warehouse?"
Data warehouses have been defined in many ways, making it difficult to formulate a rigorous definition. Loosely speaking, a data warehouse refers to a database that is maintained separately from anization's operational databases. Data warehouse systems allow for the integration of a variety of application systems. They support information processing by providing a solid platform of consolidated, historical data for analysis.
According to W. H. Inmon, a leading architect in the construction of data warehouse systems, “a data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management's decision making process." This short, prehensive definition presents the major features of a data warehouse. The four keywords, subject-oriented, integrated, time-variant, and nonvolatile, distinguish data warehouses from other data repository systems, such as relational database systems, transaction processing systems, and file systems. Let's take a closer look at each of these key features.
(1)Subject-oriented: A data warehouse anized around major subjects, such as customer, vendor, product, and sales. Rather than concentrating on the day-to-day operations and transaction processing of anization, a data warehouse focuses on the modeling and analysis of data for decision makers. Hence