tional database that contains only current data. Nonvolatile Nonvolatility, another primary aspect of data warehouses, means that after the informational data is loaded into the warehouse, changes, inserts, or deletes are rarely performed. The loaded data is transformed data that originated in the operational databases. The data warehouse is subsequently reloaded or, more likely, appended on a periodic basis with new, transformed or summarized data from the operational databases. Apart from this loading process, the information contained in the data warehouse generally remains static. The property of nonvolatility permits a data warehouse to be heavily optimized for query processing. Built From Scratch Because each company has its own business needs and business queries, a data warehouse database is normally built from scratch utilizing the available data warehousing enabling tools. Determining what kind of questions or queries that end-users need is the first step, though, a time consuming one. Data modeling for such a "customized" data warehouse database can then be developed. Identifying what data is needed from the operational database(s) and then populating the data warehouse would be the subsequent steps. The entire process can then be repeated as additional refinement is needed over time. From the attributes described above, it is apparent that the purpose and usage of an operational database and a data warehouse vary greatly. The chart below summarizes these differences: CategoryOperational DatabaseData WarehouseFunctionData processing, support of business operations Decision supportDataProcess oriented, current values, highly detailedSubject oriented, current and historical values, summarized and sometimes detailed UsageStructured, repetitiveAd-hoc, some repetitive reports and structured applications ProcessingData entry, batch, OLTPEnd-user initiated queries Figure 1: Operational Databases vs. Data Warehouses Deviation from th...
