DA0-002 Data Concepts and Environments Practice Question
Which TWO of the following are examples of data transformation? (Choose TWO.)
⚠ Common exam trap
CompTIA often tests the distinction between data transformation (changing format/structure) and data cleansing (removing errors/duplicates) or data analysis (generating summaries), leading candidates to mistakenly select removal of duplicates or summary statistics as transformations.
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
✓
Normalizing data to eliminate redundancy
Data normalization is a transformation process that reorganizes data to reduce redundancy and improve integrity, typically by decomposing tables into smaller, related tables (e.g., achieving 3NF in relational databases). This changes the structure and representation of the data, which is a core example of data transformation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Normalizing data to eliminate redundancy
Why this is correct
Normalization is a transformation.
- ✗
Creating a backup of the database
Why it's wrong here
Backup is a data protection activity.
- ✓
Converting string dates to date format
Why this is correct
Type conversion is transformation.
- ✗
Generating summary statistics
Why it's wrong here
This is data summarization.
- ✗
Removing duplicate records
Why it's wrong here
This is data cleansing.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.