DA0-002 Data Acquisition and Preparation Practice Question
A data engineer is profiling a dataset of customer orders and notices that the 'order_date' column contains values in multiple formats: 'YYYY-MM-DD', 'MM/DD/YYYY', and 'DD-Mon-YYYY'. The column is currently stored as a string. Which action should the engineer take to ensure consistent date handling for analysis?
⚠ Common exam trap
The trap here is thinking that a query-time CASE statement is sufficient, but it leaves the data inconsistent and burdens every future query with conversion logic.
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
✓
Parse each format and load the dates into a new column with a consistent DATE data type.
The engineer should parse each date format and load the values into a new column with a consistent DATE data type. This standardizes the data at the storage level, ensuring all analytical queries and tools interpret dates uniformly. It also allows the use of native date functions and avoids repeated conversion logic in every query.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a CASE statement to convert each format to a standard date type during queries.
Why it's wrong here
While a CASE statement can handle multiple formats at query time, it is inefficient and error-prone, especially as data volume grows. It also does not fix the underlying inconsistency, meaning every query must replicate the logic. This approach is a temporary workaround rather than a robust data preparation step, and it complicates downstream analysis.
- ✗
Replace all delimiters with hyphens to make the strings look uniform.
Why it's wrong here
Simply replacing delimiters does not resolve the underlying order of date components. For example, 'MM/DD/YYYY' and 'DD-MM-YYYY' would become ambiguous if both use hyphens. This approach could introduce new errors and does not create a true date type. It is a superficial fix that fails to address the core inconsistency.
- ✗
Leave the column as string and rely on the BI tool to interpret the formats.
Why it's wrong here
Relying on the BI tool to interpret mixed formats is risky because different tools may parse them inconsistently or fail entirely. It pushes the problem to the presentation layer and can lead to incorrect aggregations or filtering. The data remains ambiguous and error-prone, undermining trust in the analysis. Standardizing at the source is always preferable.
- ✓
Parse each format and load the dates into a new column with a consistent DATE data type.
Why this is correct
Parsing the various string formats and storing the result in a DATE column enforces consistency at the storage layer. This ensures all downstream queries and tools interpret the dates correctly without additional conversion logic. It also enables date-specific functions and comparisons. This is the most reliable way to standardize date data for 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
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.