Git-based SQL → Preset Datasets (Native GitHub Integration)

What is the problem or goal the end user is trying to solve or accomplish?

Customers want to author SQL in Git (version-controlled, code-reviewed), and have Preset automatically create or update Virtual Datasets whenever those SQL files change—without building and maintaining custom CI/CD glue.

How are they solving it currently?

Custom GitHub Actions / GitLab CI pipelines that read .sql files and call the Preset API to create/update datasets.

Using Preset CLI only for migrations (export/import), then manual edits for dataset SQL.

Manual copy/paste of SQL into Preset.

What is the recommended solution by the Customer?

1. A first-party Preset ↔ GitHub integration that:

• Connects a repo/branch and path pattern (e.g., datasets/**/*.sql) to a workspace.

• On commit/merge, creates or updates Virtual Datasets in a chosen database/schema.

• Reads dataset config from a simple YAML header in each SQL file (e.g., table_name, database_id, schema, owners, tags).

• Supports dry-run/validation, error reporting in the PR, and rollbacks to a prior commit.

• Optional: multi-provider (GitLab/Bitbucket), environment mapping (Staging → Prod), and run logs visible in Preset