Data Reviewer Workflow
Review data changes in pull requests using Recce. Your admin set up Recce for your team - here's how to use it as a reviewer.
Goal: Review and approve data changes in PRs with confidence.
Prerequisites
- Recce Cloud account (via team invitation)
- Access to the project in Cloud
- PR with Recce validation results
Reviewing a PR
1. Find the Data Review Summary
When a PR modifies dbt models, the Recce Agent posts a summary comment:
- Open the PR in GitHub/GitLab
- Scroll to the Recce bot comment
- Review the summary sections
Expected result: Summary shows change overview, impact analysis, and validation results.
2. Understand the Summary
The summary includes:
| Section | What It Shows |
|---|---|
| Change Overview | Which models changed and the type of change |
| Impact Analysis | Downstream models affected by the changes |
| Validation Results | Schema diffs, row counts, and check outcomes |
| Recommendations | Suggested actions based on findings |
3. Explore in Cloud
For deeper investigation:
- Click Launch Recce in the PR comment (or go to Cloud)
- Select the PR session from the list
- Explore the changes interactively
What you can do:
- View lineage diff to see affected models
- Drill into schema changes per model
- Run additional data diffs (row count, profile, value)
- Execute custom queries to investigate specific concerns
4. Review Validation Results
Check each validation result:
- Pass - Change validated successfully
- Warning - Review recommended but not blocking
- Fail - Issue detected that needs attention
For failures, click through to see: - What was compared - Expected vs actual results - Specific differences found
5. Approve or Request Changes
Based on your review:
Approve the PR:
- Validation results meet expectations
- Impact scope is understood and acceptable
- No unexpected data changes
Request changes:
- Validation failures need investigation
- Impact scope is broader than expected
- Questions about specific changes
Leave comments referencing specific validation results to help the developer address issues.
Common Review Scenarios
Schema Changes
When columns are added, removed, or modified:
- Check if downstream models are affected
- Verify the change is intentional
- Confirm breaking changes are coordinated
Row Count Differences
When record counts change:
- Determine if the change is expected
- Check if filters or joins were modified
- Verify the magnitude is reasonable
Performance Impact
When models are refactored:
- Compare query complexity
- Check for unintended full table scans
- Review impact on downstream refresh times
Verification
Confirm you can review PRs:
- Open a PR with Recce validation results
- Find the Recce bot comment
- Click Launch Recce to open the session
- Navigate the lineage and view a diff result
Next Steps
- Data Developer Workflow - How developers validate changes
- Admin Setup - Organization and team setup
- Checklist - Track validation checks across PRs
- Share Validation Results - Share findings with your team