Data quality use cases

Learn how to use GX to address key data quality issues.

A comprehensive data quality strategy relies on a multidimensional approach to achieving and maintaining high-quality data. GX enables you to define and validate data quality checks across a variety of data quality and observability dimensions.

Distribution

Validate that data values adhere to expected ranges.

Freshness

Verify that data is available within expected timeframes.

Integrity

Validate relationships and dependencies between data.

Missingness

Identify gaps in data to maintain data completeness.

Schema

Verify that data structure conforms to established rules.

Uniqueness

Validate that distinct values are present only once.

Volume

Validate that record quantity falls within expected bounds.