2020•Auerbach Publications eBooksRequires access

Advanced Relational Database Modeling

Gavin Powell

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Abstract

This chapter focuses on the concepts of relational database modeling, normalization, and normal forms by introducing the opposite of normalization, which is denormalization and data warehousing. Dynamic static relationships are created by adding a new table containing static data and removing repeated static values from transactional tables. A data warehouse model looks a little bit more real world and business oriented than an Online Transactional Processing (OLTP) normalized data model. A data warehouse consists of facts and dimensions, which are two different types of tables. Each data warehouse structure consists of a single fact table surrounded by multiple dimensions. An active OLTP database may have all older transactions deleted from its active files on a periodical basis — annually for instance.

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What this paper is about

This chapter focuses on the concepts of relational database modeling, normalization, and normal forms by introducing the opposite of normalization, which is denormalization and data warehousing. Dynamic static relationships are created by adding a new table containing static data and removing repeated static values from transactional tables. A data warehouse model looks a little bit more real world and business oriented than an Online Transactional Processing (OLTP) normalized data model. A data warehouse consists of facts and dimensions, which are two different types of tables. Each data warehouse structure consists of a single fact table surrounded by multiple dimensions. An active OLTP database may have all older transactions deleted from its active files on a periodical basis — annually for instance.

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Available abstract

This chapter focuses on the concepts of relational database modeling, normalization, and normal forms by introducing the opposite of normalization, which is denormalization and data warehousing. Dynamic static relationships are created by adding a new table containing static data and removing repeated static values from transactional tables. A data warehouse model looks a little bit more real world and business oriented than an Online Transactional Processing (OLTP) normalized data model. A data warehouse consists of facts and dimensions, which are two different types of tables. Each data warehouse structure consists of a single fact table surrounded by multiple dimensions. An active OLTP database may have all older transactions deleted from its active files on a periodical basis — annually for instance.

Key concepts: Relational database, Computer science, Database, Relational model, Database design

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