Describe the process of mapping source data to a Clarity target model.

• A. Define source-to-target mappings, transformation rules, null handling, data quality checks, test cases, and reconciliation.
• B. Copy data without transformation.
• C. Only map table names.
• D. Ignore null handling.

Answer: (A)

Mapping source data to a Clarity target model requires a disciplined plan that specifies how every source element corresponds to a target field, what transformations are needed to align formats and business rules, and how to treat missing values. Defining source-to-target mappings creates a clear blueprint of field-to-field relationships. Transformation rules handle data type conversions, unit normalization, date parsing, lookups, and derived values so the data fits the target model's semantics. Null handling is essential because decisions about whether to propagate, default, or suppress missing values greatly influence data quality and downstream logic. Data quality checks catch invalid, inconsistent, or missing data before it enters the target, guarding reliability. Test cases validate that the mappings produce expected outputs under different scenarios and help prevent regressions. Reconciliation ensures that the amount and content of data loaded into the target matches the source intent, confirming the integration worked as planned.

Simply copying data ignores transformations and structural alignment, leaving the target with mismatched types or semantics. Mapping only table names omits column-level mappings, rules, and quality considerations. Ignoring null handling risks introducing incorrect values or surprises in downstream processes.