What are the steps to eliminate transitive dependencies in a database schema?

1 Identify transitive dependencies

The first step to eliminate transitive dependencies is to identify them in your database schema. A transitive dependency can be detected by applying the following rule: if A is the primary key, and B and C are non-key attributes, then C is transitively dependent on A if C depends on B and B depends on A. For example, suppose you have a table called Employee with the following columns: EmployeeID (primary key), Name, Department, and Manager. In this table, Manager is transitively dependent on EmployeeID, because Manager depends on Department and Department depends on EmployeeID.

3 Check for anomalies

The third step to eliminate transitive dependencies is to check for any anomalies that may arise from the changes you made to your database schema. Anomalies are problems that affect the consistency and accuracy of your data, such as insertion, deletion, or update anomalies. For example, an insertion anomaly occurs when you cannot insert a new record without providing values for all the attributes, even if some of them are irrelevant or unknown. A deletion anomaly occurs when you delete a record and unintentionally lose some related information. An update anomaly occurs when you update a value and have to change it in multiple places, creating inconsistency or redundancy. To avoid these anomalies, you should ensure that your database schema follows the rules of normalization, such as having a single primary key for each table, storing only one value per column, and avoiding repeating groups or derived attributes.

4 Test your queries

The final step to eliminate transitive dependencies is to test your queries on your new database schema and compare the results with your original schema. You should verify that your queries return the same or better results, and that they are efficient and accurate. You should also check for any errors or warnings that may indicate a problem with your data or your schema. For example, you can use the EXPLAIN command in SQL to analyze the execution plan of your queries and see how they use indexes, joins, filters, and other operations. You can also use tools such as performance monitors, data validators, or query optimizers to improve your queries and your database schema.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?