olap - 1 On-Line Application Processing Warehousing Data...

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Unformatted text preview: 1 On-Line Application Processing Warehousing Data Cubes Data Mining 2 Overview Traditional database systems are tuned to many, small, simple queries. Some new applications use fewer, more time-consuming, analytic queries. New architectures have been developed to handle analytic queries efficiently. 3 The Data Warehouse The most common form of data integration. Copy sources into a single DB ( warehouse ) and try to keep it up-to-date. Usual method: periodic reconstruction of the warehouse, perhaps overnight. Frequently essential for analytic queries. 4 OLTP Most database operations involve On-Line Transaction Processing (OTLP). Short, simple, frequent queries and/or modifications, each involving a small number of tuples. Examples : Answering queries from a Web interface, sales at cash registers, selling airline tickets. 5 OLAP On-Line Application Processing (OLAP, or analytic) queries are, typically: Few, but complex queries --- may run for hours. Queries do not depend on having an absolutely up-to-date database. 6 OLAP Examples 1. Amazon analyzes purchases by its customers to come up with an individual screen with products of likely interest to the customer. 2. Analysts at Wal-Mart look for items with increasing sales in some region. Use empty trucks to move merchandise between stores. 7 Common Architecture Databases at store branches handle OLTP. Local store databases copied to a central warehouse overnight. Analysts use the warehouse for OLAP. 8 Star Schemas A star schema is a common organization for data at a warehouse. It consists of: 1. Fact table : a very large accumulation of facts such as sales. Often insert-only. 2. Dimension tables : smaller, generally static information about the entities involved in the facts. 9 Example : Star Schema Suppose we want to record in a warehouse information about every...
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olap - 1 On-Line Application Processing Warehousing Data...

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