Premium Only Content
Data Quality Dimensions (v1.11)
Tired of writing custom SQL just to understand where your data quality issues are coming from? Collate's new Data Quality Dimensionality feature in version 1.11 lets you test data quality at the dimensional level with just a few clicks.
What You'll Learn:
How to create column-level tests with dimensions to analyze data quality across different categorical values (like status, region, or product type)
The difference between traditional column-level tests and dimensional tests, and why dimensionality gives you crucial insights into where problems actually originate
How to use impact scores to quickly identify which dimensions are carrying the most failures, saving you hours of investigation time
Demo Highlights:
Watch a live walkthrough creating dimensional tests on a Redshift table, comparing gift card amounts across different status values
See the new dimensionality tab in action, revealing test results broken down by each dimension value with clear pass/fail indicators
Learn how to analyze historical execution patterns for specific dimensions to spot trends and prevent future issues
This feature eliminates the need for brittle, custom SQL code that requires constant maintenance. Instead, you get an intuitive interface that provides an additional layer of granularity, exposing problems you might have missed with traditional testing approaches. Whether you're managing data quality for analytics, compliance, or operational systems, dimensional testing helps you understand not just that there's a problem, but exactly where it's happening.
Perfect for data engineers, analytics engineers, and anyone responsible for maintaining high-quality data pipelines. Stop guessing where your data quality issues are hiding and start pinpointing them with precision.
Learn more about Collate: https://www.getcollate.io/
Try Collate's Managed OpenMetadata Service with Demo Data: https://sandbox.open-metadata.org/
#dataquality #DataObservability #OpenMetadata #Collate #DataEngineering #DataGovernance #Redshift #MetadataManagement #DataTesting #DimensionalTesting
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