--- title: 'Some of You Will "Git" This' description: Pull requests, diffs, hooks, tests and pipelines - for your production data. Data Controller brings the git workflow to master data management in SAS. date: '2026-08-13 14:00:00' author: 'Data Controller' authorLink: https://www.linkedin.com/showcase/data_controller tags: - Announcements previewImg: './gitflow.png' --- # Some of You Will "Git" This If you could make a "pull request" for production data, how might that look? Perhaps: - ✅ A before / after comparison of the values that had changed ([the approvals screen](https://docs.datacontroller.io/dc-userguide/)) - ✅ Security (who can submit / approve in each "repo") ([EDIT vs APPROVE groups](https://docs.datacontroller.io/dcc-security/)) - ✅ Only store the changed data (not full copies) - ✅ A new "diff" when the base table changes - ✅ Ability to choose one or more approvers ([`NUM_OF_APPROVALS_REQUIRED`](https://docs.datacontroller.io/dcc-tables/)) - ✅ HOOK scripts before / after a commit ([pre/post edit and approve hooks](https://docs.datacontroller.io/dcc-tables/)) - ✅ Tests (DQ checks) prior to merge ([validation rules](https://docs.datacontroller.io/dcc-validations/)) - ✅ A pipeline following a merge ([post-approve hooks](https://docs.datacontroller.io/dcc-tables/)) - ✅ Emails for "status" changes ([email alerts](https://docs.datacontroller.io/emails/)) - ✅ Comments by reviewers - ✅ Full history of changes ([the History tab](https://docs.datacontroller.io/dc-userguide/)) Sound familiar? This is exactly how developers have managed *code* for decades - and Data Controller brings the same discipline to *data*. Every edit to a table in SAS® goes through an edit - stage - approve workflow: changes are staged as a diff, checked by validation rules and hook scripts, reviewed and approved by the people you choose, then loaded. The audit trail captures who changed what, when and why - the `git blame` of master data. If you're ready to "commit" to Data Control, we invite you to "clone" the latest version of [Data Controller for SAS®](https://datacontroller.io) - which has ALL these features - and "push" to your "main" environment for some "master" data management!