Choosing the right quality metric
A junior engineer at Global Retail Analytics runs the cleaning pipeline on a fresh online_retail upload but accidentally comments out the na.drop(subset=["CustomerID"]) line. The remaining steps - na.fill(), dropDuplicates(), and the invalid-record filter - all run without errors.
Which quality check metric would immediately reveal the mistake?
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Data Transformation with Spark SQL in Databricks
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