PL-300 Visualize and analyze the data Practice Question
You need to create a report that calculates running total of sales over time. Which Power BI feature should you use?
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
✓
Use the Quick Measure for 'Running total'
The correct option is A, the Quick Measure for 'Running total', because Power BI provides this built-in Quick Measure specifically to compute a cumulative sum of a value (e.g., sales) across a sorted axis such as a date, generating the required DAX automatically. It handles the filter context and ordering needed for a running total without manual coding. Option B is not the intended feature since writing a custom SUM/FILTER measure is a manual approach rather than the dedicated Power BI feature for this task. Option C is unsuitable because a calculated table is static and does not dynamically respond to report filters or slicers like a measure. Option D is incorrect because a calculated column using EARLIER computes row-level values at data refresh and cannot produce a dynamic running total in the report visual.
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 Quick Measure for 'Running total'
Why this is correct
The Quick Measure for 'Running total' automatically generates a measure that uses CALCULATE with FILTER and ALLSELECTED, capturing the current date context via MAX(Calendar[Date]) and summing values for all dates less than or equal to that point. This approach is fully dynamic: it respects slicers and filters on other columns, updates with the selected date range, and is a best practice because it leverages a proper date table and measure semantics. Unlike a calculated column or table, the generated measure is a lightweight, query-time computation that responds instantly to user interactions.
- ✗
Write a measure using SUM and FILTER
Why it's wrong here
A measure using SUM and FILTER would calculate a static total for a filtered subset of rows, not a running total that accumulates sequentially over time. This approach lacks the dynamic row-by-row evaluation across a date context, which requires a function like EARLIER or a window function such as WINDOW or DATESYTD. It is tempting because SUM and FILTER are commonly used for conditional aggregation, such as summing sales for a specific product category, where a single filtered value is needed.
- ✗
Create a calculated table with running total
Why it's wrong here
A calculated table is materialized once when the model is processed, so any running total it contains would be frozen at that point and not recalculated as users interact with the report. It cannot respond to report-level filters, slicers, or row-level security changes because it lives outside the query context. While a calculated table could technically be created using SUMMARIZE and a running-total pattern, it would not serve as a measure and would break the filter propagation required for a true dynamic running total.
- ✗
Add a calculated column using EARLIER function
Why it's wrong here
Using a calculated column with EARLIER would evaluate row-by-row during table expansion and store a static value in the table. Because calculated columns are neither measure-like nor responsive to slicers, the running total would be fixed at refresh time and would not adjust when the user filters by date, product, or other attributes. Additionally, EARLIER references a prior row context, but a sequential running total requires a filter context that iterates over all rows up to the current row, which is both inefficient and semantically incorrect for a dynamic report measure.
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