Microsoft Certified: Power BI Data Analyst AssociatePrepare the dataHard
A data analyst is performing data profiling in Power Query on a customer dataset. The 'Email' column is critical for uniqueness, but upon using 'Column profile' and 'Column quality' features, it's observed that there are several blank entries and some entries marked as 'Error'. The analyst needs to understand the exact count of these problematic entries to assess data quality. Which Power Query profiling metric provides this information directly?
- AColumn Profile
- BColumn Quality
- CColumn Statistics
- DValue Distribution
Show answer & explanationAnswer & explanation
Correct answer: B. Column Quality
The 'Column Quality' feature in Power Query Editor provides a direct, high-level overview of the column's health, showing percentages and counts for 'Valid', 'Error', and 'Empty' values. This directly addresses the need to understand the exact count of blank and error entries.
Why the other options are wrong
- A. Column Profile provides a more detailed view (including statistics and distribution), but 'Column Quality' is the specific metric that gives the summary of valid, error, and empty counts/percentages at the top of the column.
- C. Column Statistics provides numerical summaries like Min, Max, Average, Count, Distinct Count, etc., but not a direct breakdown of 'Error' and 'Empty' counts.
- D. Value Distribution shows the frequency of each unique value, not a summary of errors or blanks.
Column Quality (Power Query)
Column Quality is a data profiling feature in Power Query that provides a quick visual summary of the data health for a selected column, showing the percentage and count of valid, error, and empty (null) values.
- Shows Valid, Error, and Empty percentages/counts.
- Provides a quick overview of data health.
- Helps identify columns with significant data quality issues.
Memory trick: Quality, Stats, Distribution: the three pillars of data insight.