CISA Practice Question: Information Systems Acquisition, Development, and Implementation
During an ERP implementation, data migration is a critical activity. Which of the following controls would be most effective in ensuring the accuracy and completeness of migrated data?
⚠ Common exam trap
CISA often tests the difference between preventive, detective, and corrective controls, and the trap is choosing a tool (automated extraction) or a responsibility assignment (data owner) instead of a detective control that actually verifies accuracy and completeness.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Performing a trial migration and reconciling the results
A trial migration followed by reconciliation is the most effective control because it validates the accuracy and completeness of the migrated data by comparing source and target records before the final cutover. Reconciliation identifies discrepancies, missing records, and transformation errors, allowing correction before go-live. This directly addresses both accuracy and completeness.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Using automated data extraction tools
Why it's wrong here
Automated extraction tools move data efficiently but provide no verification that extracted records are accurate or complete. Reconciliation of source and target counts and values is required. It is tempting because automation reduces manual effort and error, and would be the right control when the objective is efficient, repeatable extraction rather than assurance.
- ✓
Performing a trial migration and reconciling the results
Why this is correct
A trial migration replicates the full extract, transform and load process against a subset, then reconciles record counts and financial totals against source systems. This detects truncation, duplication and mapping errors before go-live, directly satisfying the accuracy and completeness objective.
- ✗
Assigning a data owner for each data field
Why it's wrong here
Assigning a data owner establishes accountability for data quality but does not itself verify migrated values against source records. Accuracy and completeness require reconciliation and validation testing. It is tempting because ownership underpins ongoing data governance, and would be correct when defining stewardship responsibilities after go-live.
- ✗
Running parallel processing for one month
Why it's wrong here
Parallel processing compares new-system output against legacy processing over time, validating transaction results rather than the migrated data itself. Accuracy and completeness of migration demand record counts and field-level reconciliation. It is tempting because parallel runs do detect processing errors, and would suit validating system functionality before cutover.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official ISACA exam blueprint
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