DA0-002 Data Acquisition and Preparation Practice Question
A data analyst is merging two datasets: one containing employee details (employee_id, name, department) and another containing salary information (employee_id, salary). The employee_id in the first dataset is stored as an integer, while in the second dataset it is stored as a string with leading zeros (e.g., '00123'). The analyst attempts to join the tables on employee_id but gets no matches. What is the most likely cause of the join failure?
⚠ Common exam trap
The trap here is overlooking data type and format differences, assuming that '123' and '00123' are equivalent when they are not in a join condition.
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
✓
The employee_id data types are different, causing implicit conversion issues.
The join fails because the employee_id values are stored differently: one as integer, the other as string with leading zeros. Even if the numeric values are the same, the string representation differs, so equality comparison fails. Converting both to a consistent type and format resolves the issue.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The employee_id data types are different, causing implicit conversion issues.
Why this is correct
When joining on columns with different data types, the database may perform implicit conversion, but it can lead to unexpected results or errors. Here, integer vs. string with leading zeros means '123' does not equal '00123'. This mismatch causes the join to fail. Explicitly converting both to the same type and format is necessary for a successful join.
- ✗
The employee_id column has NULL values in both tables.
Why it's wrong here
NULL values in join keys result in no matches for those rows, but if there are non-NULL values, some matches should occur. The scenario implies that no matches at all are found, suggesting a systematic issue like type mismatch, not just some NULLs. NULLs would only affect specific rows, not the entire join.
- ✗
The join condition is missing a necessary filter on department.
Why it's wrong here
Adding a filter on department would further restrict the result set, potentially reducing matches. It would not cause a complete absence of matches unless the filter is extremely restrictive. The core issue is the join condition on employee_id, not additional filters.
- ✗
The employee_id column contains duplicate values in one of the tables.
Why it's wrong here
Duplicates would cause multiple matches, not zero matches. The scenario states no matches are returned, so duplicates are not the cause. While duplicates can be a data quality issue, they do not explain why the join produces an empty result set.
Visual reference
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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.