Ensuring Data Quality in Apache Spark | Best Practices for High Quality Data #interview #question

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1. duplicate check
2. null or empty check
3. schema validation
4. column level validation - like we should give the range of values that column should get.
5. source and target row count validation with watermark or audit tables.
6. incremental data check - like we should get only the data after the last processed time present in the metadata/audit tables

naveenammeejuri