Data Quality and Validation
Validation rules, data profiling, and catching bad data before it corrupts your system.
You've built your ETL pipeline. Data flows from source to destination. Everything works. Then one morning, your analytics dashboard shows that yesterday's revenue was negative $47 million. Or your user count jumped by 500% overnight. Or half your customer emails are "test@test.com."
The pipeline worked perfectly. It faithfully extracted, transformed, and loaded garbage data into your analytics system. The pipeline didn't fail — your data quality checks did, because you didn't have any.
Data validation is the immune system of your data infrastructure. Without it, bad data flows through your system silently, corrupting everything it touches.
The Five Dimensions of Data Quality
Data quality isn't just "is this value correct?" It's a multidimensional assessment:
Completeness —
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