Implement and Manage Data Quality Constraints in Unity Catalog DP-750 Practice Questions (Page 5)

Questions 21–25

1. 21application · medium

   A financial services company receives daily CSV files from a third-party data provider. The `amount` field is expected to be a decimal, but occasionally the provider sends values with currency symbols or text. The team wants to ensure that only rows with a valid decimal `amount` are written to the `transactions` table, and they want to log any rejected rows for investigation. Which approach should they use?

   • AUse a CHECK constraint `amount IS NOT NULL` on the table, which will reject rows with null but not rows with non-decimal strings.
   • BUse a Lakeflow pipeline with an expectation that `amount` is of type decimal, and set `onViolation` to 'warn' so the pipeline continues but logs violations.
   • CUse a SELECT statement with `TRY_CAST(amount AS DECIMAL(10,2))` and filter out rows where the cast is null, then write only the valid rows.
   • DSet the table schema to require `amount` as a decimal and rely on schema enforcement to reject the entire file if any value is invalid.
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2. 22expert · hard

   A healthcare company has a Lakeflow pipeline that ingests patient records. The `patient_id` must be non-null and `age` must be between 0 and 120. The team wants to ensure that invalid records are not written to the target table, but they also want to capture the invalid records for a data quality report. What is the best approach?

   • AUse a `FILTER` transformation to separate valid and invalid rows, write valid rows to the target table, and write invalid rows to a quarantine table.
   • BDefine an expectation with `onViolation = 'fail'` to stop the pipeline and then manually investigate the source data.
   • CAdd a CHECK constraint on the target table and rely on it to reject invalid rows, then query the table for invalid rows.
   • DSet `onViolation = 'warn'` in the expectation and write all rows to the target table.
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4. 23foundation · easy

   Which of the following best describes a data cardinality check?

   • AEnsuring that column data types match the declared schema
   • BEnsuring that the number of distinct values in a column matches the expected cardinality
   • CEnsuring that values in a column fall within a specified numeric range
   • DEnsuring that a column contains no NULL values
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5. 24application · medium

   A telecommunications company runs a Lakeflow Spark Declarative Pipeline that ingests call detail records into a Unity Catalog table. The source schema occasionally adds new columns. The data engineer wants to ensure the pipeline continues to run without manual intervention when new columns appear, while still maintaining data quality checks on the existing columns. What should be configured?

   • AUse a view that selects only the known columns and ignore new columns.
   • BDisable schema evolution and manually update the pipeline every time a new column appears.
   • CSet the pipeline to fail when schema drift is detected and alert the team.
   • DEnable schema evolution on the target table and keep the existing expectations unchanged.
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6. 25foundation · easy

   Which constraint type in Unity Catalog enforces that all values in a column are unique?

   • AUNIQUE constraint
   • BCHECK constraint
   • CNOT NULL constraint
   • DFOREIGN KEY constraint
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