DA0-002 Visualization and Reporting Practice Test 10 — 15 Questions

Question 1

A data analyst is presenting a story about why customer churn increased last quarter. They start by showing the current churn rate, then identify a key event (a pricing change), and finally show the impact of a proposed retention campaign. This structure follows which narrative arc?

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

Accepted Answer

Situation → Complication → Resolution. The Situation → Complication → Resolution arc (also called SCR) starts by establishing the current state (churn rate), introduces the disrupting event (pricing change) as the complication, and closes with the proposed action (retention campaign) as the resolution. This is the standard narrative structure for business data storytelling because it mirrors how decisions are made: context, problem, recommendation.

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Introduction → Methods → Results

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Hook → Context → Call to action

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Problem → Solution → Evidence

Question 2

A data analyst needs to visualize the relationship between advertising spend and sales revenue for 50 products. Which chart type is most appropriate?

Accepted Answer

Scatter plot. A scatter plot is the most appropriate chart type for visualizing the relationship between two continuous variables—advertising spend and sales revenue—across 50 products. It allows the data analyst to assess correlation, trends, and potential outliers by plotting each product as a point on a Cartesian plane, with advertising spend on the x-axis and sales revenue on the y-axis.

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Histogram

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Bar chart

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Pie chart

Question 3

In Looker Studio, you have a data source with daily sales and a separate data source with marketing spend. You want to create a chart that shows sales and marketing spend on the same axis, but the two sources are not joined natively. Which feature should you use to combine them?

Accepted Answer

Data blending. Data blending in Looker Studio lets you combine metrics from two different data sources in a single chart by defining a join key (dimension) shared between them. This is the native mechanism for merging unjoined sources without modifying the underlying data. It is designed exactly for scenarios like combining sales and marketing spend on the same axis.

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Filters

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Community connectors

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Calculated fields

Question 4

A data analyst is creating a dashboard and wants to maximize the data-ink ratio. Which action supports this principle?

Accepted Answer

Removing gridlines and reducing chart borders.. Removing unnecessary gridlines and decorative elements reduces non-data ink, thereby increasing the data-ink ratio. The data-ink ratio is the proportion of ink used to display data versus total ink used in the chart.

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Including detailed data tables alongside charts.

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Using 3D effects to make bars stand out.

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Adding a background image to make the dashboard visually appealing.

Question 5

A data analyst is building a Power BI report to track KPIs for a retail chain. Which TWO of the following are considered leading indicators? (Choose two.)

Accepted Answer

Customer satisfaction score. Customer satisfaction score (B) is a leading indicator because it measures how customers feel about the company's products or service, which tends to predict future repeat purchases, retention, and revenue before those financial outcomes appear. Number of website visits (C) is also a leading indicator because it reflects current interest and engagement that typically precedes conversions and sales, giving an early signal of future demand. By contrast, profit margin (D) and total sales revenue (E) are lagging indicators, since they report financial results that have already occurred. Number of employees (A) is a structural or capacity measure rather than a predictive indicator of future performance, so it does not qualify as a leading indicator here.

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Number of employees

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Profit margin

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Total sales revenue

Question 6

A data analyst wants to visualize the distribution of customer ages, including quartiles and potential outliers, for a dataset with 10,000 records. Which TWO chart types are appropriate? (Choose two.)

Accepted Answer

Box plot. A box plot (A) is correct because it directly displays the five-number summary — minimum, first quartile (Q1), median, third quartile (Q3), and maximum — along with potential outliers plotted beyond the 1.5×IQR fences, which is exactly what the analyst needs for quartiles and outliers. A histogram (E) is also correct because it bins the 10,000 age values into intervals and shows the frequency distribution, revealing shape, skew, and modality of the ages. A pie chart (B) is unsuitable because it shows parts-of-a-whole proportions for categorical data, not a numeric distribution. A line chart (C) is inappropriate since it implies a continuous sequence or trend over an ordered variable such as time, not a frequency distribution. A treemap (D) displays hierarchical part-to-whole relationships using nested rectangles, which does not convey quartiles or outliers.

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Pie chart

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Line chart

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Treemap

Question 7

A senior data analyst is advising a team on dashboard design principles. Which THREE of the following are recommended best practices? (Choose three.)

Accepted Answer

Apply consistent color coding across all charts for similar metrics.. Option A is correct because consistent color coding across all charts for similar metrics lets viewers instantly associate a color with a given measure, reducing cognitive load and preventing misinterpretation when moving between visualizations. Option C is correct because clear labels and titles give each chart an explicit metric, dimension, and unit context, so users do not have to guess what the axes or values represent. Option E is correct because maximizing the data-ink ratio by minimizing chartjunk (Tufte's principle) removes non-data elements such as redundant gridlines, 3D effects, and decorative backgrounds, keeping attention on the actual data. Option B is not recommended because plotting every data point creates clutter and obscures trends; aggregation or filtering is usually preferable. Option D is not recommended because using a variety of colors merely for visual excitement is decorative rather than informative and can confuse meaning or harm accessibility.

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Include every data point to provide complete context.

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Use a variety of colors to make the dashboard visually exciting.

Question 8

A data analyst wants to visualize the monthly sales trend for the past year. Which chart type is most appropriate?

Accepted Answer

Line chart. Line charts are best for showing trends over time.

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Bar chart

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Pie chart

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Scatter plot

Question 9

A sales manager wants to display the contribution of each product category to total revenue, with a maximum of six categories. Which chart type is most suitable?

Accepted Answer

Pie chart. A pie chart is ideal for showing the contribution of each part to a whole, especially when the number of categories is small (six or fewer). It visually represents each category's proportion of total revenue, making it easy to compare relative sizes.

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Histogram

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Box plot

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Scatter plot

Question 10

An analyst creates a dashboard with a large amount of decorative graphics and background images. According to CompTIA Data+, which design principle is being violated?

Accepted Answer

Data-ink ratio. The data-ink ratio, a concept from Edward Tufte, states that a visualization should maximize the proportion of ink used to represent actual data relative to total ink used. By adding excessive decorative graphics and background images, the analyst reduces this ratio, making the dashboard less efficient and potentially obscuring the data. CompTIA Data+ emphasizes minimizing non-data ink to improve clarity and insight extraction.

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Visual hierarchy

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Appropriate precision

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Consistent color coding

Question 11

A data analyst wants to show the correlation between advertising spend and website traffic. Which chart type should they use?

Accepted Answer

Scatter plot. A scatter plot displays each observation as a point with one variable on the x-axis (advertising spend) and another on the y-axis (website traffic), making the relationship, direction, and strength of correlation immediately visible. It's the standard chart for bivariate correlation analysis because it preserves individual data points rather than aggregating them.

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Area chart

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Bar chart

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Line chart

Question 12

In a Power BI report, a user wants to create a measure that calculates total sales for the current year up to today. Which DAX function should they use?

Accepted Answer

TOTALYTD. TOTALYTD is a time intelligence function that calculates year-to-date values.

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CALCULATE

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SUMX

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SAMEPERIODLASTYEAR

Question 13

Which chart type is best for comparing the distribution of a continuous variable across different categories?

Accepted Answer

Box plot. A box plot is ideal for comparing the distribution of a continuous variable across different categories because it displays the median, quartiles, and outliers for each category side by side. This allows for quick visual comparison of central tendency, spread, and skewness across groups. Histograms show distribution for a single variable, not across categories.

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Pie chart

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Histogram

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Treemap

Question 14

An analyst creates a scatter plot with three variables: X, Y, and a third variable represented by the size of the markers. This chart is called a:

Accepted Answer

Bubble chart. A bubble chart is a variation of a scatter plot where a third numeric variable is encoded by the size (area) of the markers. This allows the visualization of three dimensions of data simultaneously on a two-dimensional plane, making it the correct choice for the described chart.

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Heat map

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Treemap

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Waterfall chart

Question 15

A dashboard designer wants to ensure the most important KPI is prominently displayed at the top left. Which design principle is being applied?

Accepted Answer

Visual hierarchy. Visual hierarchy arranges elements by importance, typically placing the most critical information where the eye naturally starts (top left in Western cultures).

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Consistent color coding

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Data-ink ratio

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Appropriate precision