PL-300 Visualize and analyze the data Practice Test 11 — 15 Questions

Question 1

You have a Power BI dataset with a 'Sales' table that includes a 'ProductID' column. You also have a 'Products' table with 'ProductID' and 'Category' columns. You create a relationship between the tables. You want to create a measure that calculates the total sales for products in the 'Electronics' category. Which DAX expression should you use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

CALCULATE(SUM(Sales[Amount]), Products[Category] = "Electronics"). Option D is correct because CALCULATE modifies the filter context of SUM(Sales[Amount]) by applying a filter on the related Products table's Category column, and since a relationship exists between Sales and Products, the filter propagates to the Sales table to return only Electronics sales. Option A is invalid syntax: SUMX requires a table as its first argument and an expression as its second, not a boolean condition and a column. Option B is wrong because RELATED is a column-reference function that requires row context and cannot be used directly inside a CALCULATE filter argument like that. Option C returns total sales for all categories with no Electronics filter applied.

Answer

SUMX(Products, Products[Category] = "Electronics", Sales[Amount])

Answer

CALCULATE(SUM(Sales[Amount]), RELATED(Products[Category]) = "Electronics")

Answer

SUM(Sales[Amount])

Question 2

Which THREE of the following are valid methods to enhance the accessibility of a Power BI report? (Choose three.)

Accepted Answer

Provide keyboard navigation support by setting tab order.. Setting tab order in Power BI allows keyboard-only users to navigate through report visuals in a logical sequence, which is a core requirement of WCAG 2.1 success criterion 2.4.3 (Focus Order). Option C is correct because Power BI provides built-in high contrast themes that enhance readability for users with visual impairments. Option E is correct because adding alt text to visuals ensures screen readers can convey the content to visually impaired users. Option D is not considered a valid method for this question; while using a color-blind friendly palette is a good design practice, it is not specifically a method to enhance accessibility in the context of the exam. Option A is incorrect as animations can distract and are not an accessibility feature.

Answer

Add animations to visuals to draw attention.

Answer

Use a color-blind friendly palette.

Question 3

Refer to the exhibit. You have a DAX measure that calculates year-over-year sales growth. When you add this measure to a table visual with Year and Month, some rows show blank values. What is the most likely cause?

Accepted Answer

The Calendar table does not have a continuous date range, causing SAMEPERIODLASTYEAR to return blank for some months. The correct answer is D: the Calendar table does not have a continuous date range, causing SAMEPERIODLASTYEAR to return blank for some months. Time-intelligence functions like SAMEPERIODLASTYEAR require a contiguous, gap-free date column in a marked Date table; if any dates are missing, the shifted period lookup fails and the measure returns BLANK for the affected rows. Option A is wrong because SAMEPERIODLASTYEAR works at any granularity, including month, as long as the date table is continuous. Option B is wrong because a divide-by-zero would typically surface as an error or infinity, not blank, and DAX's DIVIDE handles it gracefully. Option C is wrong because an inactive Sales–Calendar relationship would break the measure for all rows, not just some months.

Answer

The measure cannot be used at the month level because SAMEPERIODLASTYEAR only works at year level

Answer

The measure is trying to divide by zero for months with no sales in the previous year

Answer

The relationship between Sales and Calendar is inactive

Question 4

You have a Power BI report with a matrix visual showing sales by region and product category. You want to allow users to expand and collapse groups. Which feature should you enable?

Accepted Answer

Drill-down mode. Drill-down mode in a matrix visual allows users to expand and collapse hierarchical levels. When a hierarchy is present, enabling drill-down mode provides expand/collapse icons on row headers, letting users interactively show or hide subcategories. Option A (page tooltips) shows tooltip pages on hover, unrelated to expand/collapse. Option C (drill-through) navigates to another report page, not within the same visual. Option D (row and column subtotals) is a formatting feature for aggregating totals, not for expanding/collapsing groups.

Answer

Page tooltips

Answer

Drill-through

Answer

Row and column subtotals

Question 5

You are designing a Power BI report page. Which two actions can you take to improve the accessibility of the report?

Accepted Answer

Add data labels to visuals. Option C is correct because adding data labels to visuals makes the underlying values directly readable on the canvas, so users who rely on screen readers or who cannot hover over data points can still access the exact numbers without needing tooltips or mouse interaction. Option D is correct because using a high-contrast theme improves readability for users with low vision or color-vision deficiencies by ensuring foreground text and visual elements stand out clearly against the background, meeting accessibility contrast guidelines. Option A is not correct because a dark background with light text is not inherently more accessible and can actually reduce readability for some users if contrast is insufficient or if it causes glare. Option B is not correct because images are not inherently inaccessible; they can be made accessible with alt text and are often useful in visuals, so avoiding them entirely is not a valid accessibility improvement. Option E is not correct because removing all tooltips reduces the information available to users rather than improving accessibility; tooltips should be retained and made keyboard-accessible instead.

Answer

Use a dark background with light text

Answer

Avoid using images in visuals

Answer

Remove all tooltips to reduce clutter

Question 6

You have a Power BI report that uses a custom visual from AppSource. The visual is not rendering correctly. Which three steps should you take to troubleshoot?

Accepted Answer

Check if the visual version is compatible with your Power BI Desktop version. Option B is correct because custom visuals from AppSource are compiled against specific Power BI API versions, so a visual built for a newer API than your Power BI Desktop build can fail to render; confirming version compatibility is a standard first troubleshooting step. Option C is correct because updating the visual to the latest version from AppSource resolves known rendering bugs and ensures you have the most recent API-compatible build. Option E is correct because custom visuals require their expected data roles/fields to be bound; if required fields are missing or mapped incorrectly, the visual will render blank or incorrectly. Option A does not belong because disabling hardware acceleration addresses general rendering glitches in Desktop, not a specific AppSource custom visual's compatibility or data-binding issues. Option D does not belong because clearing the browser cache applies to the Power BI Service in a browser, not to troubleshooting a custom visual in Power BI Desktop.

Answer

Disable hardware acceleration in Power BI Desktop

Answer

Clear the browser cache

Question 7

You are creating a Power BI report that uses a composite model with DirectQuery and imported tables. Which two considerations should you keep in mind?

Accepted Answer

Some DAX functions may have limitations when used across storage modes. Option A is correct because in a composite model, DAX functions that traverse relationships between DirectQuery and Import tables (or that rely on certain query-folding capabilities) can be limited; functions like CALCULATE, time intelligence, and some iterators may not fully translate to the source, so cross-storage-mode calculations can behave differently or be restricted. Option C is correct because when a report needs aggregations that combine data from both DirectQuery and Import sources, Power BI must query the external source and then combine results locally, which can degrade performance due to network latency, source query cost, and limited query folding. Option B is incorrect because relationships can be defined across tables of different storage modes in a composite model; that is a core capability of composite models. Option D is incorrect for the same reason—DirectQuery tables can be related to imported tables as long as the relationship is valid and the model is configured as a composite model. Option E is incorrect because measures can be created on DirectQuery tables as well as imported tables; there is no requirement that all measures reside in imported tables.

Answer

Relationships can only be defined between tables of the same storage mode

Answer

DirectQuery tables cannot be related to imported tables

Answer

All measures must be created in the imported tables

Question 8

You have a Power BI report that includes a line chart showing monthly sales. You want to add a forecast for the next six months. Which feature should you use?

Accepted Answer

Analytics pane. The Analytics pane in Power BI provides built-in forecasting capabilities for time-series data. By selecting a line chart and adding a forecast from the Analytics pane, you can configure the forecast length (e.g., six months), confidence intervals, and seasonality, enabling predictive analysis directly within the visual.

Answer

Filter pane

Answer

Format pane

Answer

Visualization pane

Question 9

You are designing a Power BI report for a sales team. They need to see their individual performance compared to team averages. You have a table with columns: Salesperson, Region, SalesAmount. Which visual best allows each salesperson to see their own value alongside the average?

Accepted Answer

Combo chart (clustered column and line) with salesperson bars and average line. The combo chart (clustered column and line) with salesperson bars and average line is correct because it plots each salesperson's SalesAmount as a column while overlaying the team average as a line on the same axis, enabling direct individual-versus-average comparison. This dual-axis visual is the standard Power BI approach for comparing categorical values against a reference measure. A clustered bar chart with an average measure would show the average as another bar per salesperson rather than a single team reference, which is misleading. A waterfall chart shows cumulative contributions or changes, not comparisons to an average. A table with conditional formatting can display numbers and color scales but does not visually juxtapose each value against the average as clearly as a combo chart.

Answer

Clustered bar chart with a measure for average

Answer

Waterfall chart

Answer

Table with conditional formatting

Question 10

Refer to the exhibit. You have a DAX measure that calculates customer lifetime value (CLV) as total revenue divided by distinct customer count. When you use this measure in a visual with Product category, you notice that the CLV values are higher than expected. What is the most likely reason?

Accepted Answer

The measure counts customers per category, but customers who buy multiple categories are counted in each category, reducing the denominator. The CLV measure is defined as total revenue divided by distinct customer count. When this measure is used in a visual with Product category, the context filters both the revenue and the customer count to that category. The DISTINCTCOUNT(CustomerID) returns the number of customers who purchased at least one product in that category. If a customer buys multiple categories, they are counted in each category's distinct count. This makes the denominator per category smaller than the total distinct customer base, leading to a higher CLV value than expected. Option A is incorrect because returns would reduce revenue, not cause higher CLV. Option C is incorrect because using COUNTROWS would count transaction rows, not distinct customers, making the denominator larger and CLV smaller. Option D is incorrect because DIVIDE handles division by zero, and the scenario does not involve zero customers.

Answer

The measure does not filter out returns

Answer

The measure should use COUNTROWS instead of DISTINCTCOUNT

Answer

The measure is dividing by zero for categories with no customers

Question 11

You are designing a Power BI report for a sales team. The team needs to see revenue by product category, but also want to view daily trends for a selected product. The data has over 10 million rows. What visual design approach minimizes report load time?

Accepted Answer

Create a drillthrough page with a line chart showing daily revenue, and use category page as source. Option D is correct because a drillthrough page keeps the main category page lightweight and only loads the daily revenue line chart when a user right-clicks a product and drills through, so the 10 million-row detail query runs on demand rather than on every page render. This design also lets the drillthrough page be filtered to the selected product, reducing the data volume processed by the line chart. Options A and C are wrong because rendering both category and daily-trend visuals on one page forces all queries, including the high-cardinality daily aggregation, to execute on initial load. Option B is wrong because bookmarks only toggle visual visibility on the same page; hidden visuals and their underlying queries can still be evaluated, so it does not reliably reduce load time.

Answer

Use a custom visual that combines both views in one chart

Answer

Use bookmarks to switch between category view and daily trend view

Answer

Place a stacked column chart showing all categories and a line chart for trend on the same page

Question 12

You want to create a measure that calculates the percentage of total sales for each product category. What DAX function should you use to get the grand total?

Accepted Answer

ALL. ALL, because it removes all filters from the specified table or column and returns the grand total across the entire dataset, which is exactly what is needed to compute each category's percentage of total sales (e.g., SUM(Sales[Amount]) / CALCULATE(SUM(Sales[Amount]), ALL(Product[Category]))). ALL is the standard DAX function for obtaining an unfiltered grand total in ratio measures. VALUES does not remove filters; it returns a single-column table of distinct values, so it cannot produce a grand total. ALLSELECTED respects filters applied outside the query (such as slicers) rather than giving the true grand total, and REMOVEFILTERS is a filter modifier used inside CALCULATE that removes filters but is not the conventional function for retrieving a grand total in this scenario.

Answer

VALUES

Answer

ALLSELECTED

Answer

REMOVEFILTERS

Question 13

You have a Power BI semantic model with a date table that has a 1:* relationship to a Sales table. You need to create a measure that shows the number of sales transactions for the last 30 days. The date table is marked as a date table. Which DAX expression should you use?

Accepted Answer

CALCULATE(COUNTROWS(Sales), DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -30, DAY)). DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -30, DAY) returns a 30-day rolling window ending at the last date in the current filter context, which is exactly what a 'last 30 days' measure requires when the model has a marked date table. Wrapping it in CALCULATE with COUNTROWS(Sales) then counts the Sales rows whose related Date values fall in that window. Option B uses DATESBETWEEN with TODAY()-30 and TODAY(), which hard-codes the window to the actual current date rather than the model's latest date and can return blank or wrong results if the data is not current. Option C uses PREVIOUSMONTH, which returns the entire prior calendar month, not a 30-day period. Option D uses DATEADD with -30 DAY, which shifts the current filter context back 30 days rather than returning a 30-day range, so it does not produce a rolling 30-day count.

Answer

CALCULATE(COUNTROWS(Sales), DATESBETWEEN('Date'[Date], TODAY()-30, TODAY()))

Answer

CALCULATE(COUNTROWS(Sales), PREVIOUSMONTH('Date'[Date]))

Answer

CALCULATE(COUNTROWS(Sales), DATEADD('Date'[Date], -30, DAY))

Question 14

Which THREE of the following are best practices when designing Power BI reports for mobile devices? (Select three.)

Accepted Answer

Create a dedicated mobile layout view. Option A is correct because Power BI Desktop provides a dedicated Mobile Layout view (View > Mobile Layout) that lets you rearrange and resize visuals specifically for phone portrait orientation without affecting the desktop canvas. Option B is correct because small phone screens and varied lighting conditions make large font sizes and high-contrast colors essential for legibility and accessibility on mobile devices. Option D is correct because limiting each page to roughly 3-5 visuals keeps the mobile layout scannable and avoids excessive vertical scrolling and slow rendering on phones. Option C is not a mobile best practice per se: custom visuals are chosen for analytical capability, not for mobile optimization, and some custom visuals render poorly or are not optimized for small screens. Option E is not recommended because stacking multiple slicers consumes scarce screen space and complicates touch interaction; mobile designs typically favor a single, well-chosen slicer or filter pane instead.

Answer

Use custom visuals for advanced analytics

Answer

Include multiple slicers for flexible filtering

Question 15

Which THREE of the following are valid considerations for choosing between Import and DirectQuery storage modes? (Select three.)

Accepted Answer

Import mode provides faster query performance for aggregated data. Option A is correct because Import mode loads a compressed copy of the data into the Power BI in-memory engine (VertiPaq), so queries against aggregated data are served from memory and are typically much faster than DirectQuery, which pushes queries to the source. Option C is correct because Import mode datasets are constrained by capacity memory limits — for example, a 1 GB dataset size limit per dataset in shared/Pro capacity — which is a genuine factor when deciding between the two modes. Option E is correct because DirectQuery sends queries directly to the underlying source at query time, so it reflects near real-time data changes without the scheduled refresh latency required by Import mode. Option B is wrong because DirectQuery does not support all DAX functions; some functions are restricted or behave differently, and certain calculated columns/measures are unsupported. Option D is wrong because DirectQuery can query large data sources — it is often chosen precisely to avoid importing huge volumes, since processing happens at the source.

Answer

DirectQuery mode supports all DAX functions without limitations

Answer

DirectQuery mode cannot query large data sources