DA0-002 Data Acquisition and Preparation Practice Question
A data engineer is profiling a newly acquired customer table before loading it into a warehouse. The table has a customer_id column that should be unique, a signup_date column stored as text in 'YYYY-MM-DD' format, and a country column with values such as 'US', 'USA', 'United States', and 'U.S.'. The engineer must document which data quality dimensions are violated and plan remediation. Which TWO actions best address the identified data quality issues? (Choose two.)
⚠ Common exam trap
The trap here is treating every anomaly as something to remove or overwrite, when the correct response is to remediate the specific quality dimension that is actually violated.
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
✓
Standardize the country values to a single reference list using a mapping table or CASE expression.
The profile reveals a consistency problem in the country column and a type-conformance problem in the signup_date column. Standardizing country values and converting the date text to a native date type both directly remediate identified defects. Deleting duplicate IDs, ignoring inconsistent labels, or fabricating missing dates either destroys valid data or hides problems instead of resolving them.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Standardize the country values to a single reference list using a mapping table or CASE expression.
Why this is correct
The country column contains multiple representations of the same country, which violates consistency. Mapping variants like 'USA', 'United States', and 'U.S.' to one canonical code resolves the inconsistency and enables reliable grouping and joins. This directly addresses the identified quality issue through a documented, repeatable transformation rather than ad hoc fixes.
- ✗
Impute missing signup_date values with the current date to avoid nulls in the column.
Why it's wrong here
Replacing missing dates with the current date fabricates information and introduces bias, since those customers did not sign up today. It also makes the column appear complete when it is not, masking the true extent of missing data. Missing values should be measured and handled with an explicit, documented strategy, not silently overwritten.
- ✗
Delete all rows where the customer_id appears more than once to enforce uniqueness.
Why it's wrong here
Blindly deleting duplicate customer_id rows would discard legitimate records and could remove the most recent or most complete version of a customer. Uniqueness violations require investigation to determine whether duplicates are true duplicates or represent distinct events. Removal without a survivorship rule causes data loss rather than improving quality.
- ✗
Leave the country values as-is because they all refer to the same country and analysts can interpret them.
Why it's wrong here
Leaving inconsistent country values intact guarantees that aggregations by country will fragment results into separate groups, producing incorrect counts and reports. Relying on human interpretation does not scale and introduces analyst-dependent errors. Consistency problems must be resolved in the data, not deferred to downstream consumers.
- ✓
Convert the signup_date text column to a native date data type during the load.
Why this is correct
Storing dates as text prevents date arithmetic, sorting, and range filtering, and it risks inconsistent formats. Casting the 'YYYY-MM-DD' strings to a native date type enforces validity and supports time-based analysis. This is a type-conformance issue, and converting the column is the appropriate remediation before the data is used downstream.
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JA
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
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.