Advanced Data Warehouse Design: From Conventional to Spatial - download pdf or read online

By Elzbieta Malinowski

A info warehouse shops huge volumes of old facts required for analytical reasons. this information is extracted from operational databases; remodeled right into a coherent complete utilizing a multidimensional version that incorporates measures, dimensions, and hierarchies; and loaded right into a information warehouse through the extraction-transformation-loading (ETL) process.

Malinowski and Zimányi clarify intimately traditional info warehouse layout, protecting particularly complicated hierarchy modeling. also, they handle cutting edge domain names lately brought to increase the features of knowledge warehouse structures, specifically the administration of spatial and temporal info. Their presentation covers diversified levels of the layout technique, similar to specifications specification, conceptual, logical, and actual layout. They comprise 3 assorted methods for requisites specification looking on even if clients, operational information assets, or either are the motive force within the necessities collecting approach, they usually convey how every one strategy ends up in the production of a conceptual multidimensional version. in the course of the booklet the suggestions are illustrated utilizing many real-world examples and accomplished by means of pattern implementations for Microsoft's research companies 2005 and Oracle 10g with the OLAP and the Spatial extensions.

For researchers this e-book serves as an advent to the cutting-edge on facts warehouse layout, with many references to extra specific assets. supplying a transparent and a concise presentation of the key ideas and result of facts warehouse layout, it could possibly even be used because the foundation of a graduate or complicated undergraduate path. The publication can assist skilled facts warehouse designers to magnify their research probabilities via incorporating spatial and temporal details. ultimately, specialists in spatial databases or in geographical info structures may gain advantage from the knowledge warehouse imaginative and prescient for development leading edge spatial analytical applications.

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This approach can be difficult and expensive for large databases and inexperienced developers. – Bottom-up design: a separate schema is built for each group of users with different requirements, and later, during the view integration phase, these schemas are merged to form a global conceptual schema for the entire database. This is the approach typically used for large databases. • Logical design, which aims at translating the conceptual representation of the database obtained in the previous phase into a particular implementation model (or logical model) common to several DBMSs.

Such research has been introduced into the database standard SQL:2003 [194, 195] under the name of the object-relational model. In addition, current database management systems such as Oracle, Informix, DB2, and PostgreSQL have also introduced object-relational extensions, although these do not necessarily comply with the SQL:2003 standard. The object-relational model preserves the foundations of the relational model, while extending its modeling power by organizing data using an object model [155].

Common DBMSs include SQL Server, Oracle, DB2, and MySQL, among others. , to ensure that schemas in upper levels are unaffected by changes to schemas in lower levels. There are two kinds of data independence. Logical data independence refers to immunity of the conceptual schema to changes in the logical schema. For example, rearranging the structure of relational tables should not affect the conceptual schema, provided that the requirements of the application remain the same. Physical data independence refers to immunity of the logical schema to changes in the physical schema.

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