DA0-002 Visualization and Reporting Practice Test 6 — 15 Questions

Question 1

Which TWO chart types are best suited to show the proportion of total sales contributed by each product category? (Select exactly two.)

Accepted Answer

Stacked bar chart. A stacked bar chart (C) is correct because it displays each product category as a segment of a single bar, so the relative size of every segment directly shows that category's share of total sales. A pie chart (D) is correct because it divides a circle into slices whose angles are proportional to each category's contribution to the whole, which is the classic way to show part-to-whole proportions. A histogram (A) is not appropriate because it bins continuous numeric data to show a frequency distribution, not category shares. A scatter plot (B) is not appropriate because it shows the relationship or correlation between two numeric variables as points. A line chart (E) is not appropriate because it is designed to show trends or changes over a continuous dimension such as time, not proportions of a total.

Answer

Histogram

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Scatter plot

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Line chart

Question 2

A dashboard designer wants to highlight the sales performance of individual sales representatives compared to team averages. Which chart type is most suitable for this comparison?

Accepted Answer

Bar chart with average line. A bar chart with an average line is the standard visualization for comparing individual categorical values (each sales rep) against a team benchmark. Each rep gets a bar whose height shows their sales, and a horizontal reference line drawn at the team average lets viewers instantly see who is above or below the mean. This combines categorical comparison with a statistical reference, which no other listed chart does.

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Scatter plot

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Pie chart

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Line chart

Question 3

An analyst creates a pie chart showing market share of four companies: A (45%), B (30%), C (15%), D (10%). A stakeholder complains that it is difficult to compare C and D. Which alternative chart should the analyst recommend?

Accepted Answer

Horizontal bar chart. A horizontal bar chart makes it easy to compare the lengths of bars for categories C (15%) and D (10%) because the bars are aligned on a common baseline and differences in length are visually precise. Pie charts are poor for comparing similar small slices, whereas bar charts excel at this task.

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Line chart

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Stacked bar chart

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Scatter plot

Question 4

A data analyst is tasked with visualizing the distribution of customer ages across different regions. The dataset contains outliers. Which chart type best displays the distribution and highlights outliers?

Accepted Answer

Box plot. A box plot is purpose-built to display distribution summary statistics—median, quartiles, and whiskers—and explicitly marks outliers as individual points beyond the whiskers. This makes it the best choice when the requirement is to show distribution across regions while highlighting outliers. Grouping box plots by region allows direct comparison of age distributions.

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Violin plot

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Histogram

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Bar chart

Question 5

An analyst is creating a report that includes multiple charts. To ensure the audience quickly grasps the key insight, which principle of data storytelling should be applied?

Accepted Answer

Use a title that states the main insight. In data storytelling, chart titles should communicate the insight, not just describe the data. A title like 'Q3 revenue dropped 12% in EMEA' tells the audience the takeaway immediately, whereas 'Q3 Revenue by Region' forces them to interpret the chart. This aligns with the principle of reducing cognitive load and leading with the message.

Answer

Avoid using titles to reduce clutter

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Include a legend for every chart

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Place the chart before any explanation

Question 6

A data visualization specialist needs to display the relationship between advertising spend and revenue for 50 product categories over 12 months. The data has many overlapping points. Which chart type best reveals the correlation and density?

Accepted Answer

Scatter plot with alpha blending. A scatter plot with alpha blending is ideal for showing the relationship between two continuous variables (advertising spend and revenue) while handling overplotting. Alpha blending makes dense clusters appear darker, revealing density and correlation patterns that would be hidden with opaque points. With 50 categories and 12 months, there are 600 data points, so overlapping is inevitable; alpha transparency solves this by allowing the viewer to see where points concentrate.

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Heatmap with revenue binned

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Line chart for each category

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Bubble chart

Question 7

A company uses a dashboard to monitor server uptime. The data is collected every minute, but the dashboard only refreshes every hour. Users see gaps in the line chart. What is the most likely cause, and how should it be fixed?

Accepted Answer

Increase the dashboard refresh rate to match data collection frequency. The dashboard refreshes hourly while data arrives every minute, so between refreshes the chart shows only the last-fetched snapshot and appears to have gaps or stale segments. Aligning the dashboard refresh interval with the data collection frequency (or at least much closer to it) ensures the chart reflects the continuous stream of one-minute data points.

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The line chart should interpolate missing data points

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Switch to a bar chart to avoid gaps

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Use a different data series with the same refresh rate

Question 8

An analyst creates a histogram of customer transaction amounts but observes that the distribution looks bimodal. Upon review, the analyst realizes that two different customer segments (retail and wholesale) were combined. Which action best addresses this?

Accepted Answer

Create two separate histograms, one for each segment. Creating two separate histograms, one for each customer segment (retail and wholesale), best addresses the bimodal distribution because it allows the analyst to see the underlying distributions of each segment clearly. Combining them into one histogram obscures the distinct patterns, while separating them reveals the true characteristics of each group. This is a fundamental principle of data visualization: when data contains subgroups, disaggregating can provide more meaningful insights.

Answer

Use a single histogram with two colors for segments

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Use a box plot instead of a histogram

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Increase the number of bins to see more detail

Question 9

A data analyst wants to show the relative proportions of defects by type in a manufacturing process. There are 6 defect types. Which chart is most appropriate?

Accepted Answer

Pie chart. A pie chart is standard for showing parts of a whole, especially with few categories. Bar chart is also possible but not the best for proportions. Scatter and line charts are not for proportions.

Answer

Line chart

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Stacked bar chart

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Scatter plot

Question 10

Which TWO of the following are best practices for designing an accessible data visualization? (Choose 2.)

Accepted Answer

Add text labels or patterns to differentiate elements. Option A is correct because adding text labels or patterns (e.g., hatching, shapes, or direct data labels) provides a non-color-dependent way to distinguish data series, which is essential for users with color vision deficiencies or when charts are printed in grayscale. Option E is correct because using colorblind-friendly palettes (e.g., Okabe-Ito or ColorBrewer's colorblind-safe schemes) ensures that the chosen colors remain distinguishable for people with deuteranopia, protanopia, or tritanopia, satisfying WCAG 1.4.1 (Use of Color). Option B is incorrect because relying solely on color to convey information fails accessibility guidelines and excludes users who cannot perceive certain color differences. Option C is incorrect because 3D effects distort data perception, reduce readability, and add visual clutter without improving accessibility. Option D is incorrect because animated transitions can trigger motion sensitivity issues and are not a recognized accessibility best practice for data visualization.

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Rely solely on color to convey information

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Use 3D effects to make charts visually appealing

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Include animated transitions between views

Question 11

Which TWO of the following chart types are appropriate for showing the distribution of a continuous variable? (Choose 2.)

Accepted Answer

Box plot. A box plot (option A) is correct because it summarizes the distribution of a continuous variable using the median, quartiles, and potential outliers, directly revealing spread and skewness. A histogram (option E) is also correct because it bins a continuous variable into intervals and displays the frequency distribution, showing shape, center, and spread. Bar charts (option B) are for comparing categorical frequencies, not continuous distributions. Pie charts (option C) show proportions of a whole for categorical data. Line charts (option D) are used to display trends over time or ordered sequences, not the distribution of a single continuous variable.

Answer

Bar chart

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Pie chart

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Line chart

Question 12

Which THREE of the following are common mistakes when creating data visualizations? (Choose 3.)

Accepted Answer

Using a 3D pie chart. Option B is correct because 3D pie charts distort the proportions of slices through perspective and depth, making values harder to compare accurately and adding visual clutter that misleads viewers. Option D is correct because bar charts encode value by bar length, so a non-zero baseline breaks that proportional encoding and visually exaggerates or shrinks differences between categories. Option E is correct because truncating the y-axis (especially on line or bar charts) compresses or magnifies the visible range, which can manufacture trends or differences that are not meaningful in the underlying data. Options A and C are not mistakes but best practices: choosing the correct chart type for the data ensures the visual encoding matches the data relationship, and labeling axes clearly gives viewers the units, scale, and context needed to interpret the chart correctly.

Answer

Choosing the correct chart type for the data

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Labeling axes clearly

Question 13

The exhibit shows a SQL query result intended for a bar chart of revenue by region. However, the chart shows only the top 10 regions, but the query returns all regions. What is the most likely cause?

Accepted Answer

The visualization tool has a default limit on the number of categories displayed. The SQL query itself returns all regions because there is no LIMIT clause. However, the visualization tool has a built-in default limit on the number of categories displayed, such as top 10, which truncates the data in the chart. This is the most likely cause, making Option B correct. Options A, C, and D are incorrect: the GROUP BY clause is correctly specified, a WHERE clause is not required to get all regions, and the ORDER BY clause may be applied for sorting but the tool's limit overrides the full result set.

Answer

The GROUP BY clause is incorrect

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The query is missing a WHERE clause

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The ORDER BY clause is ignored in the chart

Question 14

The exhibit shows log entries. A data analyst wants to visualize the frequency of each error type over time. Which chart type is most appropriate?

Accepted Answer

Time series line chart. A time series line chart plots error frequency on the y-axis against time on the x-axis, directly showing how each error type's occurrence changes over time — exactly what the analyst needs. Line charts are ideal for trend analysis and can display multiple error types as separate lines for comparison. This makes temporal patterns (spikes, trends, seasonality) immediately visible.

Answer

Bar chart of error types

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Scatter plot of timestamp vs error code

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Pie chart of error types

Question 15

A company wants to show the number of products sold across different categories: Electronics, Clothing, Home Goods, and Books. Which chart type is most appropriate?

Accepted Answer

Bar chart. A bar chart is ideal for comparing a quantitative measure (number of products sold) across a small number of discrete categories (Electronics, Clothing, Home Goods, Books). The length of each bar directly encodes the value, making comparisons easy and accurate.

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Scatter plot

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Line chart

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Pie chart