DA0-002 Visualization and Reporting Practice Question
Exhibit
Refer to the exhibit. Tableau Workbook Log: Sheet: Sales by Region Mark Type: Map Latitude: [Region.Latitude] Longitude: [Region.Longitude] Color: SUM(Profit) Tooltip: Region, SUM(Sales), SUM(Profit) Error: Some regions display as null.
A data analyst is troubleshooting a map visualization that shows null values for some regions. Which TWO actions should the analyst take to resolve the issue?
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
✓
Check that latitude and longitude fields are properly geocoded.
Option A is correct because a map visualization plots marks using geographic coordinates, so if latitude and longitude fields are missing, malformed, or not properly geocoded, the tool cannot place those regions and renders null or blank locations. Option B is correct because if the underlying data source lacks the region names (or uses names that don't match the geocoding dictionary), the map cannot resolve those regions to coordinates, again producing null values. Option C is wrong because filtering out nulls merely hides the affected regions rather than fixing the missing geographic data, so the visualization would still be incomplete. Option D is wrong because changing the mark type to Pie abandons the map entirely and does not address the geocoding or data completeness problem. Option E is wrong because removing the color encoding from profit only affects color, not the missing geographic positions that cause the null regions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Check that latitude and longitude fields are properly geocoded.
Why this is correct
Map visualisations plot coordinates, so null regions arise when latitude and longitude values are missing or ungeocoded. Verifying geocoding ensures each region resolves to a valid point, satisfying the requirement to eliminate nulls caused by absent spatial data rather than missing region labels.
- ✓
Verify that the data source includes all region names.
Why this is correct
Null regions can result from the underlying dataset omitting certain region names, leaving no rows to plot. Confirming the data source contains every region ensures the map has complete coverage, satisfying the requirement to resolve nulls caused by missing source records rather than geocoding errors.
- ✗
Add a filter to exclude null values.
Why it's wrong here
Filtering out nulls hides the affected regions entirely, so the map still cannot display them; the stem asks for values to appear, not disappear. Filtering suits suppressing known-irrelevant rows, but here the nulls signal a data-join or region-name mismatch that must be corrected at source.
- ✗
Change the mark type from Map to Pie.
Why it's wrong here
Pie marks cannot be plotted on a geographic map, so switching mark type discards the spatial dimension that produces the regional nulls. It is tempting because pie charts display proportions clearly, and would be the correct choice for comparing category shares in a non-spatial view.
- ✗
Remove the color encoding from profit.
Why it's wrong here
Removing the colour encoding leaves the null regions still null; the missing geographic or profit data, not the colour shelf, causes the blanks. It is tempting because colour legends often look broken, and dropping colour would be right when the encoding itself misleads, for example an inappropriate diverging palette.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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