DA0-001 Visualizing Data Practice Test 5 — 15 Questions

Question 1

Refer to the exhibit. A data analyst attempts to visualize the dataset but receives a permission error. The analyst's username is 'analyst2'. What is the most likely cause?

Accepted Answer

The analyst's username is not in the users list. The policy lists only 'admin' and 'analyst'; 'analyst2' is not included, so access is denied.

Answer

The analyst lacks write permission

Answer

The analyst lacks read permission

Answer

JSON syntax error prevents parsing

Question 2

Refer to the exhibit. What is the best corrective action to resolve this error?

Accepted Answer

Convert the 'revenue' column to numeric data type during ETL. The error indicates a data type mismatch; converting the column to numeric in the ETL process ensures compatibility.

Answer

Change the chart type to a bar chart

Answer

Remove the 'revenue' column from the visualization

Answer

Use a string-compatible chart type

Question 3

Refer to the exhibit. A stakeholder complains that the line chart exaggerates the changes in sales. What is the most likely cause?

Accepted Answer

The y-axis does not start at zero. Setting beginAtZero to false truncates the y-axis, making small changes appear larger.

Answer

There are too few data points

Answer

The data labels are incorrect

Answer

The chart type should be a bar chart

Question 4

A company needs to visualize monthly sales revenue for the past five years to identify seasonal trends. Which chart type is most appropriate?

Accepted Answer

Line chart with months on the x-axis and revenue on the y-axis. Option B (Line chart) is correct because line charts are ideal for showing trends over time. Option A (Bar chart) could work but is less effective for continuous time series. Option C (Pie chart) is for proportions, not trends. Option D (Scatter plot) is for relationships between two variables.

Answer

Stacked bar chart showing each year as a segment

Answer

Scatter plot with revenue vs. month number

Answer

Pie chart for each year showing revenue distribution

Question 5

A data analyst is designing a dashboard for executives. Which best practice should be followed regarding the placement of key performance indicators (KPIs)?

Accepted Answer

Place the most important KPIs in the top-left corner. Option C is correct because placing the most important KPIs at the top-left follows natural reading patterns. Option A is wrong because cramming many charts reduces readability. Option B is wrong because color coding alone is insufficient. Option D is wrong because hiding KPIs defeats the purpose.

Answer

Include as many charts as possible on a single screen to avoid scrolling

Answer

Hide KPIs behind filters to reduce initial load time

Answer

Use distinct colors to highlight all KPIs equally

Question 6

A data analyst creates a bar chart to compare average customer satisfaction scores across five departments. The chart shows very tall bars for three departments and very short bars for two departments, making differences hard to assess. What is the most likely cause and the best fix?

Accepted Answer

The y-axis does not start at zero; reset it to zero. Option A is correct because a truncated y-axis can exaggerate differences, and starting at zero provides accurate perspective. Option B is wrong because changing chart type doesn't fix the axis issue. Option C is wrong because 3D charts distort perception. Option D is wrong because outliers should be handled properly, not necessarily by truncating.

Answer

The chart should group departments by region to reduce variance

Answer

The data should be visualized as a line chart instead

Answer

The bar chart should be replaced with a 3D version for better depth

Question 7

A business analyst wants to compare the proportion of total sales contributed by each product category in the current year. Which visualization is most suitable?

Accepted Answer

Pie chart. Option C is correct because a pie chart effectively shows parts of a whole when the number of categories is small. Option A is for trends. Option B is for distribution of a continuous variable. Option D is for relationships.

Answer

Scatter plot

Answer

Line chart

Answer

Histogram

Question 8

An analyst creates a dashboard with multiple visualizations. Which feature allows users to change the data displayed across all charts simultaneously?

Accepted Answer

Filter or slicer. Option D is correct because a filter (or slicer) can apply to multiple visuals. Option A is for limited data view. Option B is a chart type. Option C is dividing data into segments.

Answer

Linked chart

Answer

Drill-down

Answer

Data segmentation

Question 9

A data scientist creates a box plot of employee salaries and notices many outliers above the upper whisker. What action should be taken to best understand the salary distribution?

Accepted Answer

Investigate the outliers to determine if they are data entry errors or valid extremes. Option A is correct because investigating outliers may reveal legitimate high salaries or data errors. Option B is wrong because removing outliers without cause can bias results. Option C is wrong because trimming changes the distribution. Option D is wrong because a histogram may not highlight outliers clearly.

Answer

Replace the box plot with a histogram of the salaries

Answer

Remove all outliers to create a more typical box plot

Answer

Trim the top 5% of salaries and recreate the box plot

Question 10

A logistics company has data on delivery times (continuous) and distance traveled (continuous). They want to visualize the relationship between these two variables. Which chart type is most appropriate?

Accepted Answer

Scatter plot. Option D is correct because scatter plots show the relationship between two continuous variables. Option A is for categorical comparisons. Option B is for trends over time. Option C is for frequency distribution.

Answer

Histogram

Answer

Bar chart

Answer

Line chart

Question 11

A dashboard designer needs to ensure that color choices are accessible to users with color vision deficiencies. Which practice should be followed?

Accepted Answer

Combine color with patterns or labels to convey information. Option C is correct because patterns or shapes provide alternative ways to distinguish data. Option A is wrong as relying only on hue is problematic. Option B is wrong because grayscale loses emphasis. Option D is wrong as specific colors like red-green are problematic for some.

Answer

Use a rainbow color palette to maximize differentiation

Answer

Convert all charts to grayscale

Answer

Use red and green to indicate positive and negative values

Question 12

Which TWO actions will improve the readability of a bar chart showing quarterly sales across five regions?

Accepted Answer

Sort bars in descending order of sales. Options B and D are correct. Sorting bars by sales (B) helps compare values easily. Adding data labels (D) provides exact numbers. Option A is wrong because a 3D chart distorts perception. Option C is wrong because a vertical gridline pattern can clutter. Option E is wrong because a line chart on the same axis mixes data types.

Answer

Overlay a line chart showing cumulative sales

Answer

Add vertical gridlines for every bar

Answer

Switch to a 3D bar chart to add visual depth

Question 13

Which THREE are best practices for designing a dashboard for executive consumption?

Accepted Answer

Ensure the dashboard is responsive for mobile devices. Options A, C, and E are correct. Prioritize key metrics (A), provide interactive filters (C), and ensure mobile responsiveness (E). Option B is wrong because daily updates may be too frequent and clutter the dashboard. Option D is wrong because summary views are more useful for executives.

Answer

Include detailed raw data tables for transparency

Answer

Use a separate chart for each metric to avoid clutter

Question 14

Which TWO are common mistakes when creating data visualizations?

Accepted Answer

Using excessive 3D effects that obscure data. Options A and D are correct. Truncated axis (A) can mislead, and excessive 3D effects (D) distort data. Option B is wrong because using a legend is good. Option C is wrong because sorting alphabetically can be helpful for lookup. Option E is wrong because color-blind friendly palettes are a best practice.

Answer

Sorting categories alphabetically in a bar chart

Answer

Choosing a color-blind friendly palette

Answer

Including a legend to identify chart elements

Question 15

A retail company with 500 stores across North America wants to visualize its sales performance. The dataset includes store ID, region (Northeast, Southeast, Midwest, West), product category (Electronics, Clothing, Home Goods), monthly sales (in dollars), and date (from January 2018 to December 2023). The data has missing values for about 5% of store-month combinations, and a few stores have reported sales that are 10 times higher than the average for their region due to grand opening events. The goal is to create a dashboard that shows monthly sales trends for each region and product category, and allows users to identify which categories are driving growth. Which approach should the analyst take?

Accepted Answer

Create a line chart with month on the x-axis, sales on the y-axis, and separate lines for each region and category; check for outliers and consider annotating them. Option A is correct because using a line chart with time on x-axis and grouping by region and category shows trends clearly. Handling outliers separately (e.g., annotation) preserves data integrity. Option B is wrong because combining all categories in a stacked bar makes it hard to see individual trends. Option C is wrong because removing outliers discards valid grand opening data. Option D is wrong because a scatter plot is not appropriate for time series.

Answer

Use a stacked bar chart showing total sales by month, with each bar segmented by region and category

Answer

Create a scatter plot of sales vs. month with dots colored by region

Answer

Remove all stores with outlier sales and then create a line chart of the cleansed data

DA0-001 Visualizing Data Practice Test 5 — 15 Questions

Exhibit

DA0-001 Visualizing Data Practice Test 5 — 15 Questions

Exhibit