DA0-001 Communicating Data Insights Practice Test 2 — 15 Questions

Question 1

A data analyst creates a bar chart showing monthly sales for the current year. The CEO asks to see the same data but grouped by region. Which chart type is most appropriate for this new requirement?

Accepted Answer

Grouped bar chart. A grouped bar chart is the most appropriate choice because it allows the CEO to compare monthly sales across different regions side by side within each month. This chart type effectively displays two categorical variables (month and region) and one quantitative variable (sales), making it easy to see both regional performance and monthly trends simultaneously.

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Pie chart

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Stacked bar chart

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Line chart

Question 2

A data analyst creates a dashboard for operational metrics. The operations team reports that the dashboard is confusing because it shows too many metrics on one screen. Which design principle should the analyst apply?

Accepted Answer

Apply progressive disclosure. The correct answer is A because progressive disclosure is a design principle that presents only the most critical information initially, with the option to reveal additional details as needed. This directly addresses the operations team's complaint of too many metrics on one screen by reducing cognitive load and allowing users to drill down into specific metrics when required. In dashboard design, this is often implemented through expandable sections, hover-over tooltips, or click-through layers.

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Increase white space

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Use a single chart type

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Add more filters

Question 3

An analyst presents a report to stakeholders who are not data-savvy. The report includes a box plot showing the distribution of customer satisfaction scores. One stakeholder asks, 'What do the whiskers mean?' Which communication strategy should the analyst use?

Accepted Answer

Explain that the whiskers show the range of typical scores, like the spread of data.. Option A is correct because it uses plain language ('range of typical scores') to explain whiskers to a non-technical audience, aligning with the DA0-001 domain of communicating data insights effectively. The whiskers in a box plot typically extend to the minimum and maximum values within 1.5 times the interquartile range (IQR), representing the spread of data without outliers, which is accurately described as 'typical scores' for stakeholders who are not data-savvy.

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Provide a handout with definitions of box plot elements.

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Replace the box plot with a bar chart of average scores.

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State that the whiskers represent the minimum and maximum values excluding outliers.

Question 4

A data analyst needs to present the results of a customer segmentation analysis to the marketing team. The analysis identified four segments based on purchasing behavior. Which visualization is most effective for showing the characteristics of each segment?

Accepted Answer

Radar chart. A radar chart is the most effective visualization for comparing multiple quantitative variables across different categories, such as the purchasing behavior characteristics of each customer segment. It allows the marketing team to see the profile of each segment at a glance by plotting each characteristic on a separate axis radiating from a central point, making it easy to identify strengths, weaknesses, and similarities between segments.

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Histogram

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Heatmap

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Scatter plot

Question 5

An analyst is creating a report to show the relationship between advertising spend and website traffic over the past 12 months. The data has a few outliers due to special promotional events. Which chart type should the analyst use to clearly show the trend while minimizing the impact of outliers?

Accepted Answer

Scatter plot with a trend line. A scatter plot with a trend line (Option D) is the best choice because it plots each data point individually, allowing the analyst to see the overall relationship between advertising spend and website traffic while the trend line (often a linear regression line) smooths out the influence of outliers. This chart type minimizes the visual impact of extreme values by focusing on the central tendency and direction of the data, making it ideal for identifying trends over 12 months despite promotional event spikes.

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Pie chart

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Bar chart

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Heatmap

Question 6

During a presentation, a stakeholder questions the validity of a data insight because the sample size appears small. The analyst knows the sample is statistically significant. What is the best way to address this concern?

Accepted Answer

Explain the margin of error and confidence interval used.. Option B is correct because it directly addresses the stakeholder's concern by explaining the statistical concepts of margin of error and confidence interval, which demonstrate that the sample size is sufficient for the desired level of precision. This approach validates the data insight's reliability without dismissing the stakeholder's valid question, aligning with best practices in communicating data insights.

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Ignore the question and continue the presentation.

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Ask the stakeholder to trust the analysis and move on.

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Agree to collect more data before finalizing the report.

Question 7

Which TWO actions are appropriate when creating a data visualization for a diverse audience with varying levels of data literacy? (Choose two.)

Accepted Answer

Use clear and descriptive axis labels.. Clear and descriptive axis labels ensure that all viewers, regardless of their data literacy level, can understand what the axes represent. This directly supports accessibility and reduces misinterpretation, which is critical when presenting to a diverse audience.

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Use only one chart type throughout the report.

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Include interactive elements like drill-downs for all charts.

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Include a legend only if there are more than three data series.

Question 8

Which THREE elements should be included in a data insight report to ensure it is actionable? (Choose three.)

Accepted Answer

The level of confidence or statistical significance.. Option A is correct because an actionable data insight report must include the level of confidence or statistical significance to allow decision-makers to assess the reliability of the findings. Without this, stakeholders cannot determine whether the observed patterns are likely to be real or due to random chance, which is critical for making data-driven decisions.

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The source code of the analysis scripts.

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All raw data used in the analysis.

Question 9

You are a data analyst at a retail company. Your team has deployed a new dashboard that displays real-time inventory levels across all warehouses. The dashboard uses a traffic light color scheme (green = sufficient, yellow = low, red = out of stock). After one week, the warehouse managers complain that the dashboard is overwhelming because it shows all 500+ products at once, and they cannot quickly identify which items need immediate attention. They request a way to prioritize items that are red or yellow. Additionally, the dashboard updates every second, causing the screen to flicker constantly, which they find distracting. You need to redesign the dashboard to address these issues. Which course of action should you take?

Accepted Answer

Add a filter to show only items with red or yellow status, and reduce the refresh rate to every 5 minutes.. Option A is correct because it directly addresses both user complaints: adding a filter to show only red/yellow items reduces cognitive overload by hiding the 500+ products that are not critical, and reducing the refresh rate from every second to every 5 minutes eliminates distracting screen flicker while still providing near-real-time inventory updates. This approach balances usability with the need for timely alerts without overwhelming the user.

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Replace the dashboard with a static table that shows all products sorted alphabetically, and increase the refresh rate to every 2 seconds.

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Remove the color scheme and display only numerical values, and keep the refresh rate at 1 second.

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Add additional colors to distinguish more inventory levels and increase the refresh rate to every 500 milliseconds.

Question 10

A data analyst needs to present findings to a non-technical executive audience. Which visualization type is most appropriate to communicate a clear comparison of sales performance across multiple regions for the current quarter?

Accepted Answer

Bar chart. A bar chart is the most appropriate choice because it excels at comparing discrete categories (regions) using a common baseline, making it easy for a non-technical audience to quickly see which regions performed best or worst in the current quarter. The vertical or horizontal bars provide a clear, direct visual comparison of sales performance without requiring interpretation of trends or correlations.

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Scatter plot

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Line chart

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Heatmap

Question 11

Which TWO of the following are best practices when creating a data visualization for a presentation to stakeholders?

Accepted Answer

Including interactive filters when possible to allow stakeholders to explore data. Option A is correct because interactive filters (e.g., slicers, parameter controls) empower stakeholders to drill down into specific data subsets, ask ad-hoc questions, and uncover insights without overwhelming the initial view. This aligns with the principle of user-driven exploration, which is a best practice for stakeholder presentations where different audience members may have varying interests. Including interactivity also reduces the need for multiple static charts, keeping the presentation concise while still offering depth.

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Placing the legend at the bottom of the chart

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Using 3D effects to make the chart visually appealing

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Using only one type of chart throughout the presentation for consistency

Question 12

You are a data analyst at a retail company. The marketing team has asked you to analyze the effectiveness of a recent email campaign. You have data on email open rates, click-through rates, and conversion rates. The campaign targeted 50,000 customers; 20,000 opened the email, 5,000 clicked a link, and 500 made a purchase. The marketing director wants to know the campaign's overall performance and whether the email content was engaging. You prepare a dashboard but notice that the click-through rate (CTR) is 25% and the conversion rate is 10%, which seem high. Upon reviewing the data, you discover that the click-through rate was calculated as (clicks / opens) * 100, and the conversion rate as (purchases / clicks) * 100. The director expects the conversion rate to be calculated as (purchases / opens) * 100. Which action should you take to ensure accurate communication of insights?

Accepted Answer

Present both conversion rates (purchases/opens and purchases/clicks) with clear labels and definitions.. Option A is correct because the marketing director expects conversion rate as purchases/opens, but the analyst initially used purchases/clicks. Presenting both metrics with clear labels ensures transparency and avoids misinterpretation, allowing the director to see the full funnel performance. This aligns with best practices in data communication, where stakeholders may have different definitions of a metric.

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Change the conversion rate calculation to purchases/opens without informing the director.

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Recalculate the click-through rate as opens/sent to align with industry standards.

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Present the dashboard as is, because the calculations are technically correct.

Question 13

Drag and drop the steps to conduct a hypothesis test in the correct order.

Question 14

Drag and drop the steps to perform a root cause analysis on data quality issues in the correct order.

Question 15

Match each ETL process step to its description.