DA0-001 Communicating Data Insights Practice Test 3 — 15 Questions

Question 1

Match each data security concept to its description.

Question 2

A data analyst is creating a dashboard for executives to show monthly sales trends over the past year. Which chart type is most appropriate?

Accepted Answer

Line chart. A line chart is the most appropriate choice because it excels at showing continuous data trends over time, such as monthly sales over a year. The x-axis represents the time dimension (months), and the y-axis represents sales values, allowing executives to easily identify upward or downward trends, seasonality, and inflection points. This aligns with the goal of communicating data insights clearly and effectively.

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Stacked bar chart

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Scatter plot

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Pie chart

Question 3

An analyst is presenting findings to a non-technical audience. The data shows a 20% increase in customer churn after a price change. Which presentation approach is BEST?

Accepted Answer

Use a simple bar chart comparing churn before and after. Option C is correct because a simple bar chart visually and intuitively communicates the 20% increase in churn to a non-technical audience without requiring statistical literacy. This approach aligns with best practices for presenting data insights to stakeholders who need clear, actionable takeaways rather than technical details.

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Explain the p-value

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Provide the raw data table

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Show a complex statistical model

Question 4

A healthcare organization must ensure patient data privacy when sharing reports with external auditors. Which practice is most important?

Accepted Answer

Use pseudonymization. Pseudonymization replaces identifying information with pseudonyms, allowing data utility while protecting privacy. Aggregation reduces granularity but may still reveal identities; encryption secures transport but not the content; obtaining consent is impractical for large datasets.

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Encrypt the report file

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Obtain consent from patients

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Aggregate data at low granularity

Question 5

A dashboard automatically refreshes every hour, but users report stale data. What is the most likely issue?

Accepted Answer

The refresh interval is too long. The most likely issue is that the refresh interval is too long. If the dashboard refreshes every hour but users are seeing stale data, the data source may update more frequently than the dashboard's refresh cycle, causing a lag between data changes and dashboard updates. This is a common scheduling mismatch in BI tools like Tableau or Power BI where the refresh interval must align with data source update frequency.

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The dashboard is not published

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The dashboard uses cached data

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The data source connection is broken

Question 6

When creating a data story, what should be the FIRST step?

Accepted Answer

Identify the key message. The first step in creating a data story is to identify the key message because the entire narrative, data selection, and visualization choices must align with a central insight. Without a clear message, subsequent steps like gathering data or designing layouts risk being unfocused and failing to communicate actionable findings. This ensures the story is driven by the insight, not by the data or tools.

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Design the layout of the report

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Gather all available data

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Choose visualization tools

Question 7

A data analyst includes a map showing customer locations by zip code. The map reveals exact addresses for a few customers due to data granularity. This violates which principle?

Accepted Answer

Anonymization. The map reveals exact addresses for a few customers due to the granularity of zip code data. This directly violates the principle of anonymization, which requires that data be processed in such a way that individuals cannot be identified. By exposing precise locations, the data is no longer anonymized, as it allows re-identification of specific individuals.

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Informed consent

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Data minimization

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Data quality

Question 8

A report uses red and green colors to indicate performance; a stakeholder who is colorblind complains. What is the BEST remedy?

Accepted Answer

Add patterns or labels in addition to color. Option C is correct because adding patterns or labels alongside color ensures that the data encoding is accessible to colorblind viewers without removing the informational value of color for those who can see it. This approach follows WCAG (Web Content Accessibility Guidelines) 2.1 Success Criterion 1.4.1, which requires that color is not the sole means of conveying information. In data visualization tools like Tableau or Power BI, this is implemented by adding shape markers or text annotations to series, preserving the original color scheme for non-colorblind users while providing redundant encoding.

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Remove color entirely

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Change colors to blue and orange

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Use a different chart type

Question 9

An analyst needs to present quarterly sales data to the board. The CEO wants to see both overall trend and breakdown by region. Which dashboard layout is most effective?

Accepted Answer

A combination of a line chart for total and a stacked area chart for regional breakdown. Option C is correct because it simultaneously satisfies the CEO's dual requirement: a line chart clearly shows the overall quarterly sales trend, while a stacked area chart breaks down total sales by region, allowing the board to see both the aggregate performance and the contribution of each region over time. This combination leverages the strengths of each chart type—line for trend clarity and stacked area for part-to-whole relationships—without overloading the viewer with data.

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A single line chart with all regions

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A KPI card with total sales

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A table with all quarterly figures

Question 10

A company must comply with GDPR when reporting customer data. What must be included in the report?

Accepted Answer

A notice about data processing purposes. Under GDPR, when reporting customer data, the controller must provide a notice about the purposes of data processing to ensure transparency and lawful basis for processing. This is required by Article 13 of the GDPR, which mandates that data subjects be informed of the specific purposes for which their personal data is being processed. Including this notice in the report demonstrates compliance with the accountability principle.

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Customer names and emails

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The source of the data

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Data retention period

Question 11

Which TWO are best practices for data storytelling?

Accepted Answer

Start with the conclusion. Starting with the conclusion is a best practice for data storytelling because it immediately communicates the key insight to the audience, allowing them to understand the takeaway before diving into supporting details. This approach aligns with the inverted pyramid structure used in data communication, where the most critical finding is presented first to capture attention and provide context for the subsequent data. It ensures that even if the audience does not follow every detail, they still grasp the primary message.

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Use complex jargon to show expertise

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Use a single visualization to avoid confusion

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Include all data points for completeness

Question 12

A company is designing a dashboard for real-time monitoring. Which THREE considerations are most critical?

Accepted Answer

Alert thresholds. Alert thresholds (B) are critical for real-time monitoring because they define the conditions that trigger notifications when metrics exceed or fall below acceptable ranges. Without thresholds, the dashboard cannot proactively alert operators to anomalies, defeating the purpose of real-time oversight. This directly supports the domain of communicating data insights by ensuring actionable alerts are delivered promptly.

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Color palette aesthetics

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Drill-down capability

Question 13

Which TWO are common pitfalls when communicating data insights?

Accepted Answer

Using misleading scales on charts. Option B is correct because using misleading scales on charts (e.g., truncating the y-axis or using non-zero baselines) distorts the visual representation of data, leading to incorrect interpretations. This violates the principle of data integrity in data visualization, as it can exaggerate or minimize trends, making it a common pitfall when communicating data insights.

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Explaining assumptions clearly

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Including a clear call to action

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Providing context for the data

Question 14

Refer to the exhibit. An analyst runs a query to count orders in June 2023 and gets 12,345. However, a dashboard shows 12,298 for the same month. What is the most likely cause?

Accepted Answer

The dashboard includes time zone conversion. The most likely cause is that the dashboard applies a time zone conversion to the order timestamps, while the analyst's query counts orders based on UTC or a different time zone. If the dashboard converts timestamps to a local time zone (e.g., US/Eastern), orders placed near midnight UTC may fall into a different calendar day or month, causing a discrepancy of 47 orders. This is a common issue when raw data is stored in UTC but reporting tools apply a time zone offset without adjusting the query logic.

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The query has a syntax error

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The query excludes orders that were canceled

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The dashboard is using a different data source

Question 15

Refer to the exhibit. A data analyst is unable to run a query on the customers table after October 1, 2023. What is the reason?

Accepted Answer

The policy allows access only before October 1, 2023. The policy explicitly allows access only before October 1, 2023, meaning any query attempt on or after that date is denied. This is a time-based access control condition, often implemented using AWS IAM or Azure RBAC policies with a `Condition` block that checks the `aws:CurrentTime` or equivalent attribute. Since the query fails after October 1, 2023, the policy's effective date restriction is the direct cause.

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The resource name is incorrect

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The action should be READ not SELECT

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The policy denies access after October 1, 2023