If discrepancies are found in source-to-target count during ETL testing, what potential issues should be considered?
- Data Governance Policies, Data Archiving Strategies, Metadata Management, Data Validation Techniques
- Data Type Mismatch, Null Value Handling, Data Precision Loss, Data Transformation Errors
- ETL Tool Configuration Errors, Data Encryption Overhead, Data Compression Ratio
- Source Data Volume, Target Data Volume, Data Deduplication Techniques, Data Masking Performance
Discrepancies in source-to-target count during ETL testing may indicate issues such as data type mismatch, null value handling, data precision loss, or data transformation errors. Investigating these aspects helps ensure data integrity throughout the ETL process.
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