Q01 - Question
Managers want a single page that shows the most important information from a published report. When a manager selects an item on that page, they must go to the underlying report for more detail. What should you create?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. A dashboard in the Power BI service, built by pinning visuals from the report as tiles.
- B. A dashboard in Power BI Desktop with tiles that filter other tiles on the page.
- C. A scheduled refresh for the semantic model.
- D. A second report page that repeats every visual from the original report.
A is correct.
Explanation: A dashboard is a single page made of tiles. You add a tile by pinning a visual from a report in the Power BI service. Tiles are not interactive like visuals. When a user interacts with a tile, they go to the underlying report.
B is incorrect: You create dashboards in the Power BI service after you publish a report. Tiles are not interactive like visuals, so they do not filter other tiles.
C is incorrect: A scheduled refresh updates the data in a semantic model. It does not provide a high-level summary page.
D is incorrect: Report pages hold interactive visuals. Keep each page simple with related data. Repeating every visual does not give a high-level summary.
Q02 - Question
Tailwind Traders collects thousands of customer reviews, support tickets, and social media mentions. The team wants to categorize this unstructured feedback by theme and sentiment at a scale that manual analysis cannot match. Which type of analytics fits this requirement?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. Cognitive analytics
- B. Descriptive analytics
- C. Predictive analytics
- D. Prescriptive analytics
A is correct.
Explanation: Cognitive analytics uses AI to process unstructured data at a scale manual analysis cannot match. It can categorize feedback by theme and sentiment, which matches this requirement.
B is incorrect: Descriptive analytics quantifies what happened without explaining why. It does not use AI to categorize unstructured feedback by theme and sentiment.
C is incorrect: Predictive analytics uses historical patterns to estimate future outcomes. The requirement is to categorize existing feedback, not to estimate future results.
D is incorrect: Prescriptive analytics compares the likely results of different actions, such as price changes. It does not process reviews, tickets, and mentions.
Q03 - Question
You are creating a visual calculation in Power BI Desktop. You need to ensure the expression is easily distinguishable from a standard measure. What should you do?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. Omit aggregation functions such as SUM unless they are necessary.
- B. Wrap all field references in an aggregation function.
- C. Define the calculation in the semantic model first.
- D. Ensure the calculation evaluates data on an aggregated level instead of row-by-row.
A is correct.
Explanation: It is recommended to omit aggregation functions like SUM when they are not necessary. This makes it easier to distinguish between standard measures and visual calculation expressions.
B is incorrect: Adding unnecessary aggregation functions makes the expression look like a standard measure.
C is incorrect: Visual calculations are defined directly on the visual, not in the semantic model.
D is incorrect: Most visual calculations are evaluated row-by-row by default; ensuring aggregated evaluation does not help distinguish the expression from a measure.
Q04 - Question
A report author has a visual that shows order amounts, which are a continuous numeric field. The author wants to display the values in equal-sized groups so that readers can compare how many orders fall in each range. Which technique should the author use?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. Group two or more selected data points into a single category.
- B. Apply clustering to find similar data points.
- C. Create a what-if parameter.
- D. Bin the order amount field.
D is correct.
Explanation: Binning puts values into equal-sized groups. It is the technique for grouping continuous fields, such as numbers and dates.
A is incorrect: Grouping categorizes data by combining selected data points. It does not create equal-sized groups of continuous values.
B is incorrect: Clustering identifies segments of data that are similar to each other and dissimilar to the rest. It does not create equal-sized ranges.
C is incorrect: A what-if parameter supports scenario analysis. It does not organize the values in a visual into groups.
Q05 - Question
A sales manager wants each sales consultant to adjust a sales goal percentage in a report and see the resulting compensation. The report must use historical data to show potential outcomes. What should the report author create?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. A calculated column that flags unusual compensation values.
- B. A what-if parameter, by selecting New Parameter on the Modeling ribbon tab.
- C. A cluster of consultants with similar sales results.
- D. A bin for each range of sales amounts.
B is correct.
Explanation: What-if parameters support scenario analysis. They let you use historical data to analyze potential outcomes if a different scenario occurs, such as showing a consultant their compensation if they meet certain sales goals. To create one, select New Parameter on the Modeling ribbon tab.
A is incorrect: A calculated column that flags values supports outlier identification, and its results are static until the data is refreshed. It does not let consultants change a goal and see the effect.
C is incorrect: Clustering finds groups of similar data points. It does not let users test a different scenario.
D is incorrect: Binning puts continuous values into equal-sized groups. It does not calculate compensation for a chosen goal.
Q06 - Question
A report author is planning a new analytical report. The requirements include two subjects that have opposing objectives. The author wants a layout that follows good design practice. What should the author do first?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. Place both subjects on one page and reduce the size of each visual so that everything fits.
- B. Add background shapes and images to the single page so that the subjects look separate.
- C. Determine the number, sequence, and purpose of the pages, and keep the subjects on separate pages.
- D. Add more visuals to the first page so that consumers can compare the subjects directly.
C is correct.
Explanation: You can begin to design a report layout by determining the number, sequence, and purpose of the pages. You should avoid combining subjects or opposing objectives on the same page.
A is incorrect: Reducing visual size keeps the subjects on one page, which you should avoid.
B is incorrect: Background shapes and images are decorations. They do not separate subjects into pages.
D is incorrect: Adding visuals to one page increases the mix of subjects. It does not give each page a single purpose.
Q07 - Question
Business requirements for a sales report change often. The report author updates the report in several iterations. Executives use a dashboard built from the report. The dashboard must show report changes when the page is refreshed, and slicers and filters must continue to work. What should you do?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. Pin the live report page to the dashboard.
- B. Rebuild the dashboard tiles manually after each report change.
- C. Apply a custom dashboard theme after each report change.
- D. Configure a mobile layout for the dashboard.
A is correct.
Explanation: You can pin an entire report page to a dashboard as a live page. Changes you make to the report show on the dashboard when the page is refreshed. Slicers and filters still work, and the visuals have the same data as the report.
B is incorrect: Manual rebuilds add repeated work. A pinned live report page already reflects report changes when the page is refreshed.
C is incorrect: A theme changes the appearance of dashboard elements. It does not update the content from the report.
D is incorrect: A mobile layout controls how tiles are arranged for mobile devices. It does not keep dashboard content in sync with report changes.
Q08 - Question
A report author receives a request to build a sales report. A stakeholder asks the author to start creating visuals immediately and decide who will use the report later. Which reason best supports identifying the audience first?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. It helps the author create a result that the report consumer can use efficiently and that meets the consumer's needs.
- B. It determines the storage mode that the report must use.
- C. It removes the need to select a report type.
- D. It is required only when the consumers are executives.
A is correct.
Explanation: Identifying the audience is one of the most important steps in report design. It helps you create a final result that the report consumer can use efficiently and that meets that consumer's needs.
B is incorrect: The audience is not described as a factor that sets storage mode. It is used to shape the report design.
C is incorrect: You still select a report type. The audience helps you choose one, or a combination, of the dashboard, analytical, operational, and educational types.
D is incorrect: Executive, analyst, and information worker are all broad report consumer audiences. Identify the audience for each one.
Q09 - Question
Tailwind Traders wants a dashboard that shows monthly revenue predictions. The predictions must come from a time-series model trained on three years of sales data. The predictions must then be presented to the VP in an interactive report. Which two roles own these two parts of the work? (Select two.)
Domain: Visualize and analyze the data (25–30%) Type: Multiple choice
- A. Data scientist
- B. Business analyst
- C. Data analyst
- D. Data engineer
A and C are correct.
Explanation: A data scientist builds machine learning models and generates predictions, such as training a time-series model on historical sales data. A data analyst then visualizes those predictions in the interactive dashboard that stakeholders use.
B is incorrect: A business analyst defines the question and KPIs and interprets findings into recommendations. A business analyst does not train the model or build the dashboard.
D is incorrect: A data engineer builds and maintains the infrastructure that moves data from source systems into analysis-ready formats. Training the model and building the report are not part of that role.
Q10 - Question
A data analyst defines the logic that determines which sales transactions are outliers. Report consumers must see outlier results that stay current as the data changes, without waiting for a data refresh. Which approach should the analyst use?
Domain: Visualize and analyze the data (25–30%) Type: Single choice
- A. Create a calculated column that flags each transaction as an outlier or not an outlier.
- B. Use a measure or a visualization that applies the outlier logic.
- C. Create a static group by selecting data points in a visual.
- D. Use the Analyze feature to find where the distribution is different.
B is correct.
Explanation: A measure or a visualization produces dynamic results. The outlier logic is evaluated as the data changes, so the results do not depend on a data refresh.
A is incorrect: A calculated column can identify outliers, but its results are static until you refresh the data.
C is incorrect: Grouping categorizes data points that you select. It does not apply outlier logic that updates dynamically.
D is incorrect: The Analyze feature generates further analysis for a selected data point, but it does not dynamically identify outliers across the dataset as data changes.