DA0-002 Data Acquisition and Preparation Practice Question
Which THREE of the following are best practices when performing data extraction for a data pipeline?
⚠ Common exam trap
CompTIA often tests the misconception that full refreshes are always safer or simpler, but the trap is that they ignore the operational cost and scalability issues, while incremental extraction with proper error handling is the standard in production pipelines.
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
✓
Implementing error handling and logging
Implementing error handling and logging is a critical best practice in data pipeline extraction. It ensures that failures (e.g., network timeouts, authentication errors, or schema mismatches) are captured and can be diagnosed without data loss or silent corruption, which is essential for maintaining pipeline reliability and auditability.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Performing a full refresh every time
Why it's wrong here
Full refreshes are resource-intensive and should be avoided when not needed.
- ✓
Implementing error handling and logging
Why this is correct
Error handling ensures the pipeline can recover from failures.
- ✓
Documenting the extraction process
Why this is correct
Documentation aids maintenance and troubleshooting.
- ✗
Ignoring data quality issues during extraction
Why it's wrong here
Data quality should be addressed early.
- ✓
Using incremental extraction where possible
Why this is correct
Incremental extraction reduces processing time and resource usage.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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