DA0-002 Data Acquisition and Preparation Practice Question
A healthcare analytics team is acquiring a monthly extract of patient encounter records from a partner hospital. The extract arrives as a compressed CSV with a documented layout, but the team notices that the record count has dropped by roughly 15 percent compared with the prior month and that several encounters near month-end are absent. Which acquisition control should the team apply FIRST to determine whether the issue is a delivery problem or a source-system problem?
⚠ Common exam trap
The trap here is jumping to remediation or imputation when the correct first step is a reconciliation control that establishes where the shortfall occurred.
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
✓
Run a reconciliation check comparing the delivered record count and date range against the agreed extract specification and the prior month's profile.
When a recurring extract shows an unexpected volume or coverage change, the first control is reconciliation against the agreed specification and historical profile. That comparison determines whether the file is incomplete in transit or the source system produced fewer records. Only after the cause is known should the team remediate, whether by requesting a corrected file or adjusting downstream processing. Acting on downstream code or imputing data before diagnosis risks compounding the error.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Apply imputation to estimate the missing encounters so monthly reporting is not delayed.
Why it's wrong here
Imputing records that may simply not have been delivered fabricates data and contaminates clinical reporting. If the partner later resends the file, the imputed rows would need to be removed, creating reconciliation headaches. Imputation is appropriate for scattered missing values under a documented method, not for a systematic 15 percent shortfall of unknown origin.
- ✗
Escalate to the partner hospital's IT department and request a full re-extraction without further investigation.
Why it's wrong here
Escalation may eventually be needed, but requesting a re-extraction before checking the delivered file against the specification wastes the partner's time and may not address the cause. The shortfall could be a filtering error on the receiving side or an intentional change in scope. Gathering reconciliation evidence first makes the escalation specific and actionable rather than a vague complaint.
- ✓
Run a reconciliation check comparing the delivered record count and date range against the agreed extract specification and the prior month's profile.
Why this is correct
A reconciliation check establishes whether the file matches expected volume and coverage before any transformation. Comparing count and date range against the specification and the previous month isolates whether the gap is in delivery or in the source. This is a low-cost, first-line control that produces evidence for the partner conversation and prevents premature changes to downstream logic.
- ✗
Immediately rewrite the transformation jobs to handle a smaller dataset and reload the warehouse.
Why it's wrong here
Changing transformations before diagnosing the cause risks baking a temporary anomaly into permanent logic and can mask the real problem. If the missing records are later delivered, the modified jobs may double-count or mis-handle them. The scenario asks for the first diagnostic step, and altering downstream code is a remediation action that should follow, not precede, root-cause analysis.
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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 CompTIA exam blueprint
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