Canadian Health Information Management Association Practice Exam 2025 - Free CHIMA Practice Questions and Study Guide

Normalizing data tables is a crucial process in database design that focuses on reducing redundancy and improving data integrity. When data is stored in only one location, it minimizes the chances of data anomalies occurring.

Data anomalies can manifest in various forms, such as insertion, update, and deletion anomalies. Insertion anomalies happen when certain attributes cannot be inserted into the database without including other attributes. Update anomalies arise when multiple records must be updated to reflect a single change, leading to inconsistency if not all records are updated. Deletion anomalies occur when the deletion of one piece of data inadvertently removes other necessary information.

By normalizing the data tables, each piece of information is stored in a single, logical location, which directly mitigates these risks. This structured approach ensures that any changes to data are consistent throughout the database, thereby maintaining data integrity and reliability.

In contrast, the other options fail to reflect the fundamental benefits of normalization. The reduction of redundancy and susceptibility to anomalies is what primarily defines the effectiveness of normalization in database management.