DA0-002 Data Concepts and Environments Practice Question
A healthcare analytics team is building a dashboard to monitor patient vitals. They receive data from two sources: Source 1 provides 'heart rate' as an integer (beats per minute), and Source 2 provides 'blood pressure' as a ratio (systolic/diastolic, e.g., 120/80). The team wants to create a combined metric called 'cardiac stress index' that uses both heart rate and systolic blood pressure. However, they notice that heart rate data occasionally contains negative values due to sensor errors. The data governance policy requires that all data be valid and meaningful. Which action best addresses the data quality issue while preserving the data types?
⚠ Common exam trap
Watch out — candidates often choose Option A (converting to absolute values) thinking it 'fixes' the data, but this introduces false data and violates data validity, whereas the correct approach is to remove invalid records to maintain data integrity.
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
✓
Remove all records with negative heart rate values as they are invalid
Negative heart rate values are physiologically impossible and violate the data governance policy requiring valid and meaningful data. Removing these records ensures the dashboard only contains accurate, actionable data without altering the original integer data type of heart rate, preserving its numerical integrity for the 'cardiac stress index' calculation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert heart rate to absolute values (remove the negative sign)
Why it's wrong here
This would create false positive values, misrepresenting the actual data.
- ✗
Keep negative values but set them to NULL to indicate missing data
Why it's wrong here
NULLs can cause issues in calculations and reduce sample size unnecessarily.
- ✗
Change heart rate from integer to categorical (e.g., low, normal, high) to avoid negative issues
Why it's wrong here
This loses the precision needed for the index calculation.
- ✓
Remove all records with negative heart rate values as they are invalid
Why this is correct
Negative heart rates are not physiologically possible, so deletion is appropriate for data quality.
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