Database design

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Database design is the process of producing a detailed data model of a database. This data model contains all the necessary logical and physical design choices and physical storage parameters needed to generate a design in a data definition language, which can then be used to create a database. A fully attributed data model contains detailed attributes for each entity.

Overview

Database design involves classifying data and identifying interrelationships. This theoretical representation of the data is called an entity-relationship model (ER model). The process of database design includes the following steps:

Requirement Analysis

Requirement analysis is the first step in the database design process. It involves gathering the requirements of the database from stakeholders and understanding the data needs of the organization. This step is crucial for ensuring that the database will meet the needs of its users.

Conceptual Design

In the conceptual design phase, the data requirements are translated into a conceptual model using an ER model. This model includes entities, attributes, and relationships. The ER model is a high-level representation of the data and does not include any details about how the data will be stored physically.

Logical Design

The logical design phase involves converting the conceptual model into a logical model. This model is more detailed and includes the structure of the database, such as tables, columns, and relationships. The logical model is independent of any specific database management system (DBMS).

Physical Design

The physical design phase involves translating the logical model into a physical model. This model includes the actual implementation details, such as the specific DBMS to be used, indexing strategies, and storage parameters. The physical design ensures that the database will perform efficiently and meet the required performance criteria.

Normalization

Normalization is a process used in database design to minimize redundancy and dependency by organizing fields and table of a database. The main goal of normalization is to separate data into different tables to reduce data redundancy and improve data integrity. The process involves dividing large tables into smaller tables and defining relationships between them.

Denormalization

Denormalization is the process of combining normalized tables to improve database performance. This process is used when read performance is more critical than write performance. Denormalization can lead to data redundancy, but it can also reduce the number of joins needed to retrieve data, thus improving query performance.

Related Pages

See Also


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Contributors: Prab R. Tumpati, MD