Static data, also known as code, lookup, list, or reference data, plays a crucial role in relational database management systems. It represents fixed data that doesn’t change frequently, such as abbreviations for US states or guitar manufacturers. This data is referenced extensively by transactional data, providing context and meaning to the information stored in the database.

One common approach to managing static data is to create a separate table for each type of static data, assigning a unique ID to each entry. This allows transactional data to reference the ID instead of duplicating the static data itself. For example, instead of storing “United States” in every row that references the country, a separate “countries” table is created with an ID for each country.

Version controlling static data is important for several reasons:

1. Managing tight coupling with business logic

Static data is often tightly coupled with database logic, especially in poorly designed databases. For example, if a calculation relies on specific state IDs or “magic numbers” in the code, any changes to the static data can break the logic. By version controlling static data, you can ensure that the correct data is always used, avoiding potential issues and maintaining the integrity of your application.

2. Avoiding broken unit tests

Even in well-designed systems, unit tests can break if they rely on specific static data. When reviewing and testing the database as part of a continuous integration workflow, it’s important to avoid testing against production static data. By using version controlled static data or synthetic test data, you can ensure that your unit tests remain reliable and accurate.

3. Taking advantage of smaller data sets

Static data is typically smaller in volume compared to transactional data. This makes it easier to version control and store in source control repositories that aren’t designed to handle large amounts of data. By version controlling static data, you can take advantage of the benefits of source control, such as change tracking and auditing, without overwhelming the repository.

4. Tracking and auditing changes

Although static data doesn’t change frequently, it’s still important to track and audit any changes that occur. Version controlling static data allows you to see when and by whom changes were made, providing a complete history of modifications. This information can be invaluable for troubleshooting, compliance, and maintaining data integrity.

5. Using realistic data in testing environments

When building a QA database, using 100% synthetic test data may not always be ideal. Testers may be more comfortable and effective when working with data that closely resembles real-world scenarios. By synthetically generating static data or using version controlled static data, you can create test environments that reflect the characteristics of your production data, improving the accuracy and relevance of your testing.

Version controlling static data involves getting the data into a repository, managing changes, and deploying it when needed. There are various tools and techniques available to accomplish this, such as using SQL Server database static data scripts and integrating them into a continuous integration or delivery workflow.

By version controlling static data, you can ensure the consistency and reliability of your database, minimize the risk of errors and bugs, and improve the efficiency of your development and testing processes.