DA0-002 Data Governance Practice Test 5 — 15 Questions

Question 1

A data analyst discovers an anomaly in a dataset. Which two actions should be taken before reporting? (Choose TWO.)

Accepted Answer

Verify the data source and extraction process. Before reporting an anomaly, the data analyst must verify the data source and extraction process to ensure the anomaly is not due to a pipeline error, such as a misconfigured ETL job or a corrupted data feed. This step confirms data integrity and prevents false alarms based on extraction artifacts rather than genuine data issues.

Answer

Assume the anomaly is real and report it

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Immediately alert all stakeholders

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Remove the anomaly without documentation

Question 2

Refer to the exhibit. A data analyst is unable to access the dataset during weekends. Based on the policy, what is the most likely reason?

Accepted Answer

The condition restricts access to business hours only. The policy explicitly includes a condition that restricts access to business hours only (e.g., Monday–Friday, 9 AM–5 PM). Since the analyst is attempting to access the dataset during a weekend, the condition denies access regardless of the analyst's role or network location. This is a common attribute-based access control (ABAC) rule where time-based conditions are evaluated before granting permissions.

Answer

The analyst's role is not in the list

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The policy is misconfigured

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The access condition requires being on the internal network

Question 3

Refer to the exhibit. What is the impact of the validation result?

Accepted Answer

The staging table is missing the 'age' column, which may cause query errors. The validation result shows that the staging table has a different schema than the target table, specifically missing the 'age' column. This mismatch will cause query errors when attempting to insert or query data that references the 'age' column, as the staging table lacks the required column definition. The validation result explicitly flags this schema discrepancy, making option A correct.

Answer

The validation passed successfully

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Only duplicates were found

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The row counts match, so data is complete

Question 4

Refer to the exhibit. What is the best course of action for the data analyst?

Accepted Answer

Investigate source data to understand why 'Region' is missing. Missing data in a critical field like 'Region' indicates a potential data quality issue that requires root cause analysis. The data analyst should investigate the source system to determine whether the missing values result from a collection error, a transformation bug, or a legitimate null, rather than making assumptions by deleting rows or filling defaults. This aligns with the principle of data provenance and ensures that downstream insights are based on accurate, traceable data.

Answer

Change the default value to 'NA'

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Delete rows with missing 'Region'

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Ignore the warning as it is handled

Question 5

A data analyst is preparing a presentation for executive leadership. The analyst wants to highlight the correlation between marketing spend and revenue over the past year. Which visualization type is most appropriate for showing this relationship?

Accepted Answer

Scatter plot. A scatter plot is the most appropriate visualization for showing the relationship between two continuous variables—marketing spend and revenue—because it plots individual data points on an X-Y axis, allowing the analyst to visually assess correlation, trends, and outliers. This directly supports the goal of highlighting correlation, as the pattern of points (e.g., upward slope) indicates the strength and direction of the relationship.

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Pie chart

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Bar chart

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Histogram

Question 6

A business user asks a data analyst to include several charts in a weekly report. The user wants to see the trend of sales over the last 12 months at a glance. Which chart type should the analyst use?

Accepted Answer

Line chart. A line chart is the correct choice because it is specifically designed to display trends over continuous time intervals, such as sales over 12 months. The x-axis represents time (months), and the y-axis represents sales values, allowing the user to quickly see upward, downward, or cyclical patterns. This aligns with the requirement to visualize a trend at a glance, which is a core strength of line charts in data visualization.

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Stacked bar chart

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Treemap

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Pie chart

Question 7

A data analyst needs to communicate findings to a non-technical audience that is concerned with overall performance but not interested in details. Which approach is best?

Accepted Answer

Provide a summary dashboard with key KPIs. A summary dashboard with key KPIs is best because it distills complex data into visual, high-level metrics that non-technical stakeholders can quickly grasp. This approach aligns with the principle of data storytelling, where the focus is on actionable insights rather than technical details. Dashboards using tools like Tableau or Power BI allow for interactive filtering without overwhelming the audience.

Answer

Include complex model outputs

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Share raw data tables

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Use detailed statistical jargon

Question 8

A data analyst is creating a report to compare the performance of different sales regions. The report will be used by regional managers to identify areas needing improvement. Which of the following visualization techniques would be most effective?

Accepted Answer

A bar chart comparing each region's sales. A bar chart is most effective because it allows direct, side-by-side comparison of discrete categories (sales regions) using a common baseline, making it easy for regional managers to quickly identify which regions are underperforming. The vertical bars encode exact values with high perceptual accuracy, supporting the report's goal of highlighting areas needing improvement.

Answer

A line chart showing overall company sales

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A pie chart showing each region's contribution

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A scatter plot of sales vs. expenses

Question 9

During a data presentation, an audience member questions the accuracy of the data shown. Which of the following is the best way for the analyst to respond?

Accepted Answer

Provide documentation of data sources and transformation steps. Providing documentation of data sources and transformation steps directly addresses the audience member's concern about accuracy by demonstrating transparency and traceability. This approach aligns with best practices in data governance, as it allows the audience to verify the data lineage and any ETL processes that may have introduced errors. It also builds trust by showing the analyst has a clear understanding of the data pipeline.

Answer

Change the topic

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Offer to send the raw data later

Answer

Dismiss the question and continue

Question 10

A data analyst needs to create a dashboard that updates automatically every hour. The data source is a large database. Which approach minimizes performance impact?

Accepted Answer

Use incremental refresh only for new or changed data. Incremental refresh queries only new or changed records since the last refresh, drastically reducing data transfer and processing load on the large database. This approach uses change-tracking mechanisms (e.g., timestamps, CDC) to avoid full-table scans, minimizing performance impact while maintaining near-real-time updates.

Answer

Query the entire database each time

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Export the data to Excel and import

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Create a static report monthly

Question 11

A data analyst discovers a data discrepancy in a report that has already been distributed to executives. The discrepancy is due to a known bug that will be fixed next month. What is the most appropriate action?

Accepted Answer

Inform the executives of the error and its impact. Informing executives of the error and its impact maintains transparency and trust. Option A (send corrected report immediately) may cause confusion without proper context. Option B (wait for next scheduled update) delays communication and could lead to decisions based on incorrect data. Option C (ignore it) is unethical.

Answer

Send a corrected report immediately with an apology

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Wait for the next scheduled update

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Ignore it since it will be fixed soon

Question 12

An analyst is creating a data story about the decline in customer satisfaction scores. The data shows that satisfaction dropped after a software update. Which narrative structure best helps the audience understand the cause and effect?

Accepted Answer

Begin with the software update event, then show satisfaction before and after. It follows a chronological cause-and-effect narrative, starting with the software update event and then showing satisfaction scores before and after. This structure directly maps to the audience's need to understand the causal relationship, as it highlights the intervention point and the resulting change in the metric. In data storytelling, this is known as the 'before-and-after' or 'change-over-time' narrative, which is most effective for demonstrating impact.

Answer

Start with the current scores, then show historical trend

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Present all data points without a story

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Use a pie chart of satisfaction categories

Question 13

A data analyst is designing a dashboard for senior executives who need to quickly monitor key business metrics. Which TWO design principles should the analyst follow? (Choose two.)

Accepted Answer

Display only the most important KPIs. Senior executives need to monitor key business metrics at a glance, not be overwhelmed with extraneous data. Displaying only the most important KPIs ensures the dashboard is focused and actionable, aligning with the principle of delivering concise, high-level insights for quick decision-making.

Answer

Include detailed data tables for reference

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Add complex interactive filters

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Use as many colors as possible to make it visually appealing

Question 14

A data analyst is preparing a report to present to a mixed audience of technical and non-technical stakeholders. Which THREE techniques should the analyst use to ensure effective communication? (Choose three.)

Accepted Answer

Tailor the narrative to address different concerns. Tailoring the narrative to address different concerns ensures that both technical and non-technical stakeholders receive relevant insights. For non-technical audiences, the analyst should focus on business impact and high-level trends, while for technical audiences, deeper data nuances can be included. This approach aligns with the DA0-001 domain of Communicating Data Insights, where audience analysis is critical for effective data storytelling.

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Use only one chart type for consistency

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Use technical jargon to demonstrate expertise

Question 15

A data analyst is presenting a complex statistical analysis to a group of data scientists. The audience is highly knowledgeable. Which TWO approaches are most appropriate? (Choose two.)

Accepted Answer

Include technical details and methodology. Data scientists expect rigorous technical depth; including methodology and technical details aligns with their expertise and allows them to evaluate the analysis's validity. In a highly knowledgeable audience, omitting such details would undermine credibility and hinder peer review.

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Avoid mentioning uncertainty to maintain confidence

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Use basic visualizations like pie charts

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Simplify the findings to avoid confusion