We are excited to introduce Data Quality Check for Database (DB) connections — a new capability designed to improve data reliability and pipeline monitoring.
Data inconsistencies between source and destination systems can impact reporting accuracy and downstream analytics. The new Data Quality Check feature helps identify:
Mismatched record counts between source and destination systems
This enables teams to proactively monitor pipeline health and maintain data integrity.
For DB pipelines, a new 4th step — “Quality Check” has been added to the pipeline configuration flow.
Users can:
Enable or disable the quality check
Configure thresholds
Schedule checks as needed
The feature compares data between the:
Source system
Destination system
If the variance exceeds the configured threshold, an automated email notification is triggered to alert users about the discrepancy.
A dedicated History page is now available to help users monitor past quality check runs.
From the History page, users can:
View detailed comparison statistics
Track discrepancies over time
Analyse quality check execution results
Additionally, a new Schema button is available on the right side of the listing page.
The Schema comparison feature helps users compare:
Source table schema
Destination table schema
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