Data Quality
Data & Infrastructure
Measurement of data accuracy, completeness, and reliability
What is Data Quality?
High-quality data is essential for good ML results; includes checks for missing values, duplicates, schema violations, and bias.
Real-World Examples
- •Schema validation failure alerts
- •Detecting null-heavy columns
Related Terms
Learn more about concepts related to Data Quality