The Dimensional Database Model A standard, normalized, relational (Photography web hosting)
The Dimensional Database Model A standard, normalized, relational database model is completely inappropriate to the requirements of a data warehouse. Even a denormalized relational database model doesn t make the cut. An entirely different modeling technique, called a dimensional database model, is needed for data warehouses. A dimensional model contains what are called facts and dimensions. A fact table contains historical transactions, such as all invoices issued to all customers for the last five years. That could be a lot of records. Dimensions describe facts. The easiest way to describe the dimensional model is to demonstrate by example. Figure 7-1 shows a relational table structure for both static book data and dynamic (transactional) book data. The grayed out tables in Figure 7-1 are static data tables and others are tables containing data, which is in a constant state of change. Static tables are the equivalent of dimensions, describing facts (equivalent to transactions). So, in Figure 7-1, the dimensions are grayed out and the facts are not. Figure 7-1: The OLTP relational database model for books. Customer customer_id Shipper shipper_id shipper address phone email customer address phone email credit_card_type credit_card# credit_card_expiry Sale sale_id ISBN (FK) shipper_id (FK) customer_id (FK) sale_price sale_date Edition ISBN publisher_id (FK) publication_id (FK) print_date pages list_price format Publisher publisher_id name Publication publication_id subject_id (FK) author_id (FK) title Author author_id name Review review_id publication_id (FK) review_date text Subject subject_id parent_id name CoAuthor coauthor_id (FK) publication_id (FK) Rank ISBN (FK) rank ingram_units 175 Understanding Data Warehouse Database Modeling
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