Which practice helps minimize data anomalies by organizing data into related tables?

Which practice helps minimize data anomalies by organizing data into related tables?

• A. Storing all data in a single table.
• B. Using mixed data types in a column.
• C. Data normalization.
• D. Eliminating primary keys.

Answer: (C)

Organizing data into related tables is a practice called data normalization. The goal is to reduce redundancy so updates, inserts, and deletes don’t leave inconsistent or duplicated information scattered across the database. By splitting data into related tables and using keys to connect them, you can update a single piece of information in one place and have those changes propagate correctly through related records. For example, keeping customer details in one table and linking orders to that customer with a foreign key prevents repeating the same address or contact info in every order row, so changes are centralized and accurate. Storing everything in a single table leads to a lot of duplicated data and makes anomalies more likely when data changes. Using mixed data types in a column invites inconsistencies and makes it hard to enforce rules or perform reliable queries. Eliminating primary keys would remove a guaranteed unique identifier, breaking the ability to reliably relate records and enforce data integrity. Normalization intentionally uses primary and foreign keys to maintain consistent relationships across tables.

Organizing data into related tables is a practice called data normalization. The goal is to reduce redundancy so updates, inserts, and deletes don’t leave inconsistent or duplicated information scattered across the database. By splitting data into related tables and using keys to connect them, you can update a single piece of information in one place and have those changes propagate correctly through related records. For example, keeping customer details in one table and linking orders to that customer with a foreign key prevents repeating the same address or contact info in every order row, so changes are centralized and accurate.

Storing everything in a single table leads to a lot of duplicated data and makes anomalies more likely when data changes. Using mixed data types in a column invites inconsistencies and makes it hard to enforce rules or perform reliable queries. Eliminating primary keys would remove a guaranteed unique identifier, breaking the ability to reliably relate records and enforce data integrity. Normalization intentionally uses primary and foreign keys to maintain consistent relationships across tables.