# Conclusions from the data structures in Git tutorial
> Complete your Git-based data governance workflow with version control, automated validation, approval workflows, and environment promotion for data structures.
> Source: https://docs.snowplow.io/tutorials/data-structures-in-git/conclusion/
> Documentation index: https://docs.snowplow.io/llms.txt

- We have seen how snowplow-cli can be used to work with data structures from the command line
- We have applied that knowledge to build github workflows which support automated validation and publication
- We have added source applications, tracking plans and event specifications to use the same approach as data structures.

This approach provides you with:

- **Version control** for your data structures with full change history
- **Automated validation** to catch errors before they reach production
- **Approval workflows** through pull requests
- **Environment promotion** from development to production
- **Integration with tracking plans** for comprehensive data governance

You now have a complete CI/CD pipeline for managing your Snowplow data structures using industry-standard tools and practices.