6705-Data Quality Monitoring & Alerting - Storing Failed Data #221
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Conflicts: # datastacks/datastacks/pyspark/data_quality/main.py
# Conflicts: # datastacks/datastacks/pyspark/data_quality/main.py # datastacks/datastacks/pyspark/data_quality/utils.py
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
📲 What
Added logic to quarantine data that fails DQ validation checks
🤔 Why
We want bad data to be available for investigation but not available to downstream processes
🛠 How
When data fails a validation check, select the data that failed the check and write it to a separate location for investigation
👀 Evidence
TODO
🕵️ How to test
TODO
✅ Acceptance criteria Checklist