- Source control is the practice
of tracking changes to code, configuration files,
and other digital assets over time.
It's most often associated with software development,
but it also plays a critical role
in managing data processes.
When source controls apply to data pipelines,
transformation logic and reporting scripts,
it helps maintain consistency,
prevent errors, and support collaboration across teams.
At the core of source control is a version history.
This history captures every change made to a file,
along with who made it, when it was made, and why.
If a new update introduces an error or breaks a process,
teams can quickly revert it to a previous version.
This improves reliability
and allows for faster recovery from mistakes.
Source control systems like Git allow multiple people
to work on the same code base
without overriding each other's changes.
Team members can create branches
to test or build new features
separately from the main production version.
Once changes are reviewed and tested,
they can then be merged into the main branch.
This type of workflow supports structured development
and reduces the risk of introducing untested code
into production environments.
Source control also strengthens auditability.
In data projects, being able to show exactly
when a data transformation script changed and what changed
can be important for compliance,
especially when you're working with regulated data.
If a report output shifts unexpectedly,
version history can help identify
whether the logic behind that report was modified.
In addition to tracking code,
source control can also be used for documentation,
data definitions, and configuration files.
For example, a team might store
and version their data dictionary
or ETL job configurations
alongside their transformation scripts.
This keeps all related assets synchronized
and helps maintain data quality across updates.
Using source control is not just a technical best practice,
it's a safeguard for data quality.
It supports accountability, collaboration and traceability,
all of which are essential
when managing complex data systems
in fast moving environments.