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In the field of relational database design, normalization is a systematic way

Written on 2016-07-04 08:22:54 By Billy

In the field of relational database design, normalization is a systematic way of ensuring that a database structure is suitable for general-purpose querying and free of certain undesirable characteristics—insertion, update, and deletion anomalies—that could lead to a loss of data integrity.

Database normalization is a technique for designing relational database tables to minimize duplication of information and, in so doing, to safeguard the database against certain types of logical or structural problems, namely data anomalies. For example, when multiple instances of a given piece of information occur in a table, the possibility exists that these instances will not be kept consistent when the data within the table is updated, leading to a loss of data integrity.

A table that is sufficiently normalized is less vulnerable to problems of this kind, because its structure reflects the basic assumptions for when multiple instances of the same information should be represented by a single instance only. Higher degrees of normalization typically involve more tables and create the need for a larger number of joins, which can reduce performance. Accordingly, more highly normalized tables are typically used in database applications involving many isolated transactions

(e.g. an Automated teller machine), while less normalized tables tend to be used in database applications that do not need to map complex relationships between data entities and data attributes (e.g. a reporting application, or a full-text search application).

2.5.1 Introduction
There are several types of database management systems, categorized generally by how they logically store and retrieve data. The two most common types in use today are relational and hierarchical. Each type has its advantages and disadvantages, and in many organizations both types are used. Whether you choose a relational or hierarchical database management system depends largely on how you intend to use the data being stored.

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