PL-300 Calculated column Practice Question
You have a Power BI report that displays sales data by region. The report includes a map visual showing sales amount by state. You notice that some states are not displayed on the map because the state names in the data do not match the standard names used by Power BI's map visualization. For example, 'California' is correct but 'CA' is not recognized. You need to ensure all states appear correctly. Which action should you take? A. Create a calculated column that maps state abbreviations to full names using a SWITCH statement. B. Change the map visual to a filled map. C. Use the 'Data category' property to set the field to 'State or Province'. D. Add a custom map image. Which option is the best?
⚠ Common exam trap
A common trap is thinking that setting the Data Category property can fix mismatched values. In reality, Data Category only affects how Power BI interprets the field for geocoding, but the actual text values must still match standard names.
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
✓
Create a calculated column that maps state abbreviations to full names using a SWITCH statement
The scenario describes a data-quality problem: the state field contains values like 'CA' that Power BI's map engine cannot geocode, so a calculated column using SWITCH (or a lookup table) must translate abbreviations into the full standard names such as 'California' that the map service recognizes. Setting a data category (option A) only tells Power BI what kind of geographic data the field contains; it does not convert 'CA' into a recognizable state name, so the unmatched values would still fail to plot. Changing to a filled map (option D) or adding a custom map image (option C) alters the visualization type or background but does nothing to fix the underlying mismatched state values.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the 'Data category' property to set the field to 'State or Province'
Why it's wrong here
Setting the Data category property to 'State or Province' only attaches metadata to the field, telling Power BI to treat it as a geographic location; it does not recode the string values themselves. With the actual value 'CA', the geocoder still cannot distinguish California from Canada or other abbreviations, so no improvement in recognition occurs. Data category works as a hint for automatic mapping, but it cannot compensate for non-conforming values that need transformation before geocoding.
- ✓
Create a calculated column that maps state abbreviations to full names using a SWITCH statement
Why this is correct
A calculated column using SWITCH (or a lookup table) transforms the stored abbreviation into a full, canonical state name—for example, mapping 'CA' to 'California'—so the geocoder receives exactly what it expects. After the transformation, you can optionally set that new column's Data category to 'State or Province' to reinforce the mapping, but the key is that the underlying string has changed. This fixes the problem at the data layer, which is why it works regardless of the map visual type chosen.
- ✗
Add a custom map image
Why it's wrong here
Adding a custom map image does not resolve mismatches between stored state abbreviations and the geographic names Power BI’s built‑in map visual expects; it merely replaces the visual with a static image that lacks any data‑binding capability. This option tempts because custom map images can display arbitrary regions when the standard map lacks the required boundaries, but here the issue is data‑format inconsistency, not missing geography.
- ✗
Change the map visual to a filled map
Why it's wrong here
Switching to a filled map does not address the underlying data-format mismatch; both the standard map and filled map visuals rely on Bing Maps geocoding, which attempts to match each string value—such as 'CA'—to a recognized geographic entity. Because the value remains a two-letter abbreviation rather than a full state name, the geocoder returns ambiguous or unrecognized results, and the visual cannot assign states accurately. The visual type only changes how data is rendered (color-filled polygons vs. bubbles), not how location values are transformed or interpreted.
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