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Chapter 28. Overview of Data Warehousing and OLAP. Introduction, Definitions, and Terminology. Data warehouse Long-term data storage OLAP Online analytical processing DSS Decision support systems. Characteristics of Data Warehouses.
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Chapter 28 Overview of Data Warehousing and OLAP
Introduction, Definitions, and Terminology • Data warehouse • Long-term data storage • OLAP • Online analytical processing • DSS • Decision support systems
Characteristics of Data Warehouses • Modeled differently – multidimensional rather than strictly relational • Data is “cleaned” prior to transfer • Data is updated on scheduled basis, rather than as transactions happen • Used for making long-term business decisions, not for daily transactions
Data Modeling for Data Warehouses • Multidimensional models use matrices called data cubes • The relational data model can be cumbersome for the types of querying that is needed in a data warehouse. • Can query in each direction to answer questions.
Building a Data Warehouse • Needs careful design • Terms need to be standardized • For instance, F/M instead of Female/Male • Often subdivided into dependent data marts, keeping related data physically close
Problems and Open Issues in Data Warehouses • Difficulties of Implementing Data Warehouses • Open Issues in Data Warehousing
Summary • http://en.wikipedia.org/wiki/Data_warehouse