DA0-002 Visualization and Reporting Practice Test 2 — 15 Questions

Question 1

A hospital's analytics team has created a dashboard for tracking patient wait times across departments. The dashboard uses a stacked bar chart showing average wait time per department, with each bar segmented by severity level (Low, Medium, High). However, management complains that it is difficult to compare total wait times across departments or identify which department has the highest average wait time. The data itself is accurate and complete. The analyst needs to redesign the visualization to address these concerns. Which course of action should the analyst take?

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

Accepted Answer

Change the chart to a grouped bar chart, with each department having separate bars for each severity level placed side-by-side.. The core problem is that stacked bars make it hard to compare totals across departments because the segments do not share a common baseline—only the bottom segment aligns. A grouped bar chart places each severity level's bar side-by-side within each department group, so the total for each department is visually apparent (the group height) and individual severity comparisons are also easy. This directly addresses management's need to compare totals and identify the highest-wait department.

Answer

Replace the stacked bar chart with multiple line charts, one per department.

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Use a heat map with departments on one axis and severity levels on the other, with color intensity representing wait time.

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Switch to a pie chart showing the proportion of total wait time each department contributes.

Question 2

A retail company has collected data on monthly advertising spend (in thousands of dollars) and corresponding sales (in thousands of dollars) over the past 12 months. The analyst creates a scatter plot to visualize the relationship between advertising spend and sales. The plot shows a cluster of points with a positive trend, but there is one extreme outlier where spend was $100,000 but sales were only $20,000. Upon investigation, the analyst discovers that the outlier is due to a data entry error: the sales figure should have been $200,000. The analyst wants to present the overall trend accurately in a meeting. Which course of action should the analyst take first?

Accepted Answer

Remove the outlier and recreate the scatter plot.. The outlier is confirmed to be a data entry error (sales should be $200,000, not $20,000), so it does not represent a real observation. Correcting the underlying data by removing (or fixing) the erroneous point is the necessary first step before any trend analysis or visualization, because the outlier will distort the regression line and mislead the audience. Only after cleaning the data should the analyst recreate the scatter plot to show the true positive relationship.

Answer

Use a bar chart to show average sales per advertising spend bin.

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Add a trend line using linear regression to the current scatter plot.

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Change the chart type to a line chart.

Question 3

An analyst has a dataset with monthly sales figures for the past five years. They want to highlight the cumulative effect of sales over time and show the total contribution of each month stacked on top of previous months. Which chart type is most suitable?

Accepted Answer

Area chart. An area chart is the most suitable choice because it fills the space between the line and the baseline with color, visually emphasizing the cumulative total over time. This allows the analyst to see both the trend of monthly sales and the stacked contribution of each month to the overall cumulative effect, which is exactly what the question requires.

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Line chart

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Stacked bar chart

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Waterfall chart

Question 4

A data analyst is working in Looker Studio and wants to add a metric that counts the number of unique customers per month. In the context of Looker Studio, which type of field is this metric?

Accepted Answer

Metric. In Looker Studio, a metric is a field that aggregates numeric data, such as counts, sums, or averages. Counting unique customers per month requires an aggregation (COUNT_DISTINCT) applied to a numeric or identifier field, which is the defining characteristic of a metric. Dimensions are used for grouping and categorizing data, not for performing calculations like counting unique values.

Answer

Dimension

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Parameter

Answer

Blend

Question 5

A data analyst is creating a dashboard to monitor e-commerce performance. The dashboard will be used by both executives (strategic view) and operations managers (detailed view). The analyst plans to use interactive filters. Which THREE design principles or features are most important to apply for effective dashboard design?

Accepted Answer

Consistent color coding across all charts. Option A is correct because consistent color coding across all charts lets both executives and operations managers interpret the same metric (e.g., revenue always in blue, returns always in red) without relearning the legend on each visual, reducing cognitive load and misinterpretation. Option C is correct because a visual hierarchy that emphasizes the most important KPIs (e.g., largest size, top-left placement, boldest color for revenue or conversion rate) serves the executives' strategic view while still letting operations managers drill into secondary metrics. Option D is correct because interactive filters that slice data by region, date, and product directly support the stated requirement of serving two audiences with one dashboard, enabling executives to see aggregate trends and operations managers to isolate specific segments. Option B is not appropriate because annotating every data point creates clutter and defeats the purpose of a dashboard, which should surface trends and exceptions rather than exhaustively label each value. Option E is not appropriate because maximizing data-ink ratio by removing all labels and titles would strip the context needed to interpret the charts, harming comprehension for both audiences.

Answer

Including annotations on every data point

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Maximizing the data-ink ratio by removing all labels and titles

Question 6

An analyst is creating a dashboard in Power BI to track sales performance. They want to ensure that when a user selects a specific product category on a slicer, all other visuals on the page filter to show data only for that category. Which TWO actions should the analyst take?

Accepted Answer

Edit interactions between the slicer and other visuals to ensure filtering is enabled. Option B is correct because Power BI's Edit Interactions feature controls how a slicer affects each visual on the page; ensuring the interaction is set to Filter (not None or Highlight) makes the other visuals respond to the slicer selection. Option E is correct because a slicer must exist on the page and have the Category field bound to it so that selecting a category generates the filter context that propagates to the other visuals. Option A is incorrect because Sync slicers only aligns slicer selections across multiple pages, which is unnecessary when the requirement is filtering visuals on a single page. Option C is incorrect because Single select only restricts the slicer to one chosen value at a time; it does not itself propagate filtering to other visuals. Option D is incorrect because CALCULATE with ALLEXCEPT creates a DAX measure that removes filters except on specified columns, which is unrelated to slicer-driven visual filtering.

Answer

Use the 'Sync slicers' pane to synchronize the slicer across all pages

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In the 'Format' pane, set the slicer to 'Single select'

Answer

Create a measure using the CALCULATE function with ALLEXCEPT

Question 7

A data analyst needs to show the cumulative revenue over time, with emphasis on the total magnitude. Which chart type is most appropriate?

Accepted Answer

Area chart. An area chart is ideal for showing cumulative revenue over time because it fills the area under the line, visually emphasizing the total magnitude (the area itself represents the cumulative sum). The filled area makes it easy to compare the relative size of totals across different time periods or categories. Unlike a line chart, which focuses on trends, the area chart's shading draws attention to the volume or magnitude, directly addressing the requirement to emphasize total magnitude.

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Scatter plot

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Bar chart

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Pie chart

Question 8

An analyst needs to create a report in Power BI that shows year-to-date sales compared to the same period last year, with the ability to drill down from year to quarter. Which DAX function combination is most appropriate for the year-to-date calculation?

Accepted Answer

TOTALYTD and SAMEPERIODLASTYEAR. TOTALYTD computes a year-to-date aggregate over a date column, and SAMEPERIODLASTYEAR returns the equivalent date range shifted back one year, so combining them yields YTD-this-year versus YTD-last-year comparisons. Both are time intelligence functions that rely on a marked date table, which is exactly what the analyst needs for year/quarter drill-down.

Answer

CALCULATE and ALL

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SUM and FILTER

Answer

RANKX and TOPN

Question 9

An analyst needs to display the number of website visitors per age group (e.g., 18-25, 26-35, 36-45). Which chart type is most appropriate?

Accepted Answer

Histogram. A histogram is the correct choice because it is specifically designed to display the frequency distribution of continuous numerical data grouped into bins or intervals, such as age ranges (18-25, 26-35, 36-45). The bars in a histogram are adjacent (no gaps) to reflect the continuous nature of the underlying variable, and the height of each bar represents the count of observations falling within that bin. This makes it the natural fit for showing 'number of visitors per age group' where the age groups are ordered, contiguous intervals.

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Bar chart

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Line chart

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Pie chart

Question 10

A sales analyst is building a report to analyze quarterly performance. Which THREE are appropriate uses of a formula language or a data transformation tool? (Select three.)

Accepted Answer

Using a data transformation tool to remove duplicate rows from the data source. Option B is correct because a data transformation tool (such as Power Query) is specifically designed to cleanse source data, and removing duplicate rows is a standard transformation operation that improves data quality before analysis. Option C is correct because a year-to-date calculation function (e.g., TOTALYTD in DAX) is purpose-built to aggregate sales from the start of the year through the current period, which directly supports quarterly performance reporting. Option D is correct because functions like CALCULATE modify the filter context of a measure, which is a core analytical technique for producing accurate, context-aware aggregations in reports. Option A is not appropriate because an iterative summation function (e.g., SUMX) inherently performs row-by-row iteration, so describing it as summing without iteration is contradictory and technically inaccurate. Option E is not appropriate because lookup functions such as RELATED are used to retrieve a value from a related table within a calculated column, but the scenario calls for formula-language or transformation uses tied to report analysis, and this option describes a modeling operation rather than an analytical calculation.

Answer

Using an iterative summation function to sum a column without using iteration

Answer

Using a lookup function to create a calculated column from a related table

Question 11

In Power BI, a data analyst needs to create a measure that calculates total sales for the current year. Which DAX function should be used?

Accepted Answer

TOTALYTD. TOTALYTD is a DAX time-intelligence function that calculates the year-to-date total of an expression, exactly matching the requirement for 'total sales for the current year.' It takes an expression and a dates column and returns the cumulative total from the start of the year to the current filter context.

Answer

SAMEPERIODLASTYEAR

Answer

CALCULATE

Answer

SUMX

Question 12

A data analyst wants to show the monthly sales trend for the past two years with an emphasis on cumulative growth. Which chart type is most appropriate?

Accepted Answer

Area chart. An area chart is the most appropriate choice because it combines a line chart's ability to show trends over time with a filled area beneath the line, which visually emphasizes cumulative growth. For monthly sales data over two years, the area fill makes it easy to see both the month-over-month trend and the total accumulated sales volume, which is exactly what the data analyst needs.

Answer

Scatter plot

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Bar chart

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Line chart

Question 13

A data analyst wants to visualize the number of website visitors by traffic source (e.g., organic, paid social, email) and also show the proportion of each source within the total. Which chart type is best?

Accepted Answer

Stacked bar chart. A stacked bar chart is best because it allows the data analyst to display both the absolute number of visitors per traffic source and the proportional contribution of each source to the total across categories (e.g., time periods). Each bar represents the total visitors, and segments within the bar show the breakdown by source, making it easy to compare both individual source counts and their relative shares.

Answer

Histogram

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Pie chart

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Line chart

Question 14

Which of the following is a key performance indicator (KPI) tied to a strategic objective, as opposed to a metric?

Accepted Answer

Customer satisfaction score (CSAT) as a strategic goal. A key performance indicator (KPI) is a measurable value that demonstrates how effectively a company is achieving a key strategic objective. Here, 'Customer satisfaction score (CSAT) as a strategic goal' explicitly ties the metric to a strategic objective (e.g., improving customer loyalty), whereas a plain metric like 'average handle time' is an operational measure without a direct strategic link. In data visualization, KPIs are often displayed on dashboards with targets and thresholds to track progress toward high-level business goals.

Answer

Average handle time

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Number of daily logins

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Server uptime percentage

Question 15

In a Power BI report, a data analyst needs to create a measure that calculates the sum of sales only for products that have a profit margin greater than 10%. Which DAX function should be used to filter the calculation?

Accepted Answer

CALCULATE. CALCULATE is the DAX function that modifies the filter context of an expression, making it the correct choice to apply a condition like 'profit margin > 10%' to a SUM of sales. It takes an expression and one or more filter arguments, evaluating the expression under the new context. This is the canonical pattern for conditional aggregation in Power BI.

Answer

Answer

FILTER

Answer

SUMX