Database Normalisation Questions Long
In the context of database normalization, redundancy refers to the duplication of data within a database. It occurs when the same piece of information is stored in multiple places, leading to data inconsistency and inefficiency.
Redundancy can arise due to various reasons, such as denormalized database design, lack of proper data modeling, or incomplete normalization. When redundant data exists in a database, it can result in several issues:
1. Data Inconsistency: Redundant data increases the chances of inconsistencies and discrepancies. If the same information is stored in multiple locations and one of them gets updated, it becomes challenging to ensure that all instances of that data are also updated. This can lead to conflicting or outdated information, causing confusion and errors in data analysis.
2. Increased Storage Space: Storing redundant data consumes additional storage space, which can be a significant concern in large databases. This not only increases the cost of storage but also affects the overall performance of the database. Unnecessary duplication of data can slow down data retrieval and manipulation operations.
3. Update Anomalies: Redundancy can introduce update anomalies, making it difficult to maintain data integrity. For example, if a customer's address is stored in multiple tables, updating the address in one table but not in others can result in inconsistent data. This can lead to incorrect analysis, reporting, and decision-making.
4. Insertion and Deletion Anomalies: Redundant data can also cause insertion and deletion anomalies. Insertion anomalies occur when it is not possible to insert certain data into the database without providing additional, unrelated information. Deletion anomalies, on the other hand, occur when deleting a record unintentionally removes other related data.
To address these issues, normalization techniques are applied to eliminate or minimize redundancy in a database. Normalization involves breaking down a database into multiple tables and establishing relationships between them. By organizing data in a structured manner, redundancy can be reduced, and data integrity and efficiency can be improved.
Normalization follows a set of rules, known as normal forms, which guide the process of eliminating redundancy. The most commonly used normal forms are First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and Boyce-Codd Normal Form (BCNF). Each normal form has specific criteria that must be met to ensure a well-structured and non-redundant database design.
In conclusion, redundancy in the context of database normalization refers to the duplication of data within a database. It can lead to data inconsistency, increased storage space, update anomalies, and insertion/deletion anomalies. Normalization techniques are employed to eliminate or minimize redundancy, ensuring a more efficient and reliable database system.