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Introduction to Decomposition

Decomposition is the process of breaking a single relation (table) into two or more relations to eliminate redundancy, maintain data integrity, and satisfy normalization rules.

  • It is often necessary to avoid data anomalies and redundancy, particularly when dealing with large, complex databases.
  • If there is no proper decomposition of the relation, then it may lead to problems like loss of information.

To ensure that decomposition is beneficial and maintains the integrity of the database, the following properties must hold:

1.) Lossless Decomposition:

  • A decomposition is said to be lossless if, after decomposing a relation into smaller relations and then joining them back together, the original relation can be reconstructed without any loss of data.

2.) Dependency Preservation:

  • Dependency preservation ensures that all functional dependencies in the original relation are preserved in the decomposed relations. This is crucial for maintaining the same data integrity constraints as the original relation.

3.) Lack of Data Redundancy:

  • Decomposition should minimize or eliminate redundant data while maintaining data integrity and avoiding unnecessary duplication. It reduces storage requirements and avoids anomalies such as update, insertion, and deletion anomalies.

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