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Data & Analytics · Foundational

Data Quality (DQ)

The degree to which data is fit for its intended use, judged on dimensions such as accuracy, completeness, consistency, timeliness, validity and uniqueness.

Definition

Data quality management covers profiling, defining rules, monitoring, cleansing and fixing root causes at the source. Poor quality erodes trust in analytics and AI. Tools include Glue Data Quality, Dataplex data quality scans, Lakeflow expectations, dbt tests and Great Expectations.

Exam tip

Fix data quality issues at the source when possible; downstream cleansing treats the symptoms.

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