In a data migration workflow, which activity follows loading data into staging?

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Multiple Choice

In a data migration workflow, which activity follows loading data into staging?

Explanation:
After loading data into staging, the next essential step is to verify that the load happened correctly by validating the data with reconciliations. This means checking that the records, totals, and data types in the staging area match the source system, and that counts and sums align as expected. This validation catches discrepancies like missing rows, duplicate records, truncations, or datatype mismatches early, before the data moves further in the pipeline or into production. It ensures the integrity of the migrated data so that downstream ETL processes can rely on accurate input. Other steps aren’t the immediate next action after staging. Designing ETL processes is a planning/implementation activity that typically occurs earlier in the project or prior to the live load. Migrating to production happens after validation confirms the data is sound. Implementing a rollback is a risk-management measure that's used if problems are detected, but it isn’t the actual validation step that confirms data quality.

After loading data into staging, the next essential step is to verify that the load happened correctly by validating the data with reconciliations. This means checking that the records, totals, and data types in the staging area match the source system, and that counts and sums align as expected. This validation catches discrepancies like missing rows, duplicate records, truncations, or datatype mismatches early, before the data moves further in the pipeline or into production. It ensures the integrity of the migrated data so that downstream ETL processes can rely on accurate input.

Other steps aren’t the immediate next action after staging. Designing ETL processes is a planning/implementation activity that typically occurs earlier in the project or prior to the live load. Migrating to production happens after validation confirms the data is sound. Implementing a rollback is a risk-management measure that's used if problems are detected, but it isn’t the actual validation step that confirms data quality.

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