Which of the following, when used at the design stage, improves the efficiency, accuracy, and speed of a database?

Which of the following, when used at the design stage, improves the efficiency, accuracy, and speed of a database?

• A. Tokenization
• B. Data masking
• C. Normalization
• D. Obfuscation

Answer: (C)

Normalization is a process used in database design that organizes data to reduce redundancy and improve data integrity. By structuring the data into tables and ensuring that relationships between tables are established correctly, normalization enhances the efficiency of the database. This structured approach allows for faster query processing, as it reduces the amount of duplicate data and ensures that updates and modifications can be carried out without inconsistency. The process involves dividing large tables into smaller, channeled tables and defining relationships among them. This ultimately streamlines data retrieval, storage, and management, making operations more efficient. Accuracy is fortified as well since normalization helps eliminate anomalies that can arise from data duplication, ensuring that the data reflects the true state of the information being stored. In contrast, while tokenization, data masking, and obfuscation are important techniques for enhancing security and privacy, they do not inherently improve the efficiency or speed of database design. These methods are aimed more at protecting sensitive information rather than structuring or organizing data to facilitate performance improvements in the database.

Normalization is a process used in database design that organizes data to reduce redundancy and improve data integrity. By structuring the data into tables and ensuring that relationships between tables are established correctly, normalization enhances the efficiency of the database. This structured approach allows for faster query processing, as it reduces the amount of duplicate data and ensures that updates and modifications can be carried out without inconsistency.

The process involves dividing large tables into smaller, channeled tables and defining relationships among them. This ultimately streamlines data retrieval, storage, and management, making operations more efficient. Accuracy is fortified as well since normalization helps eliminate anomalies that can arise from data duplication, ensuring that the data reflects the true state of the information being stored.

In contrast, while tokenization, data masking, and obfuscation are important techniques for enhancing security and privacy, they do not inherently improve the efficiency or speed of database design. These methods are aimed more at protecting sensitive information rather than structuring or organizing data to facilitate performance improvements in the database.