DA0-002 Practice Test 2 — 10 Questions

Question 1

A dashboard designer wants to ensure the most important KPI is prominently displayed at the top left. Which design principle is being applied?

Accepted Answer

Visual hierarchy. Visual hierarchy arranges elements by importance, typically placing the most critical information where the eye naturally starts (top left in Western cultures).

Answer

Consistent color coding

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Data-ink ratio

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Appropriate precision

Question 2

A data analyst needs to share a weekly sales report with the marketing team. The report includes aggregated data from the data warehouse. To simplify access, the analyst creates a virtual table that encapsulates the complex query. Which database object should the analyst create?

Accepted Answer

View. A view is a virtual table that encapsulates a complex query, allowing users to access aggregated data without needing to understand the underlying SQL. In this scenario, the analyst creates a view to simplify access to the weekly sales report, as it presents pre-defined, aggregated data from the data warehouse as if it were a table.

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Trigger

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Stored procedure

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Index

Question 3

In SQL, you want to retrieve all products whose names start with 'Pro'. Which WHERE clause should you use?

Accepted Answer

WHERE product_name LIKE 'Pro%'. LIKE with pattern 'Pro%' matches strings starting with 'Pro' followed by any characters. '%Pro%' matches any string containing 'Pro', 'Pro_' matches 'Pro' plus one character, and 'Pro' is exact match.

Answer

WHERE product_name LIKE '%Pro%'

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WHERE product_name LIKE 'Pro_'

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WHERE product_name = 'Pro'

Question 4

Drag and drop the steps to perform a data audit in the correct order.

Accepted Answer

1. Inventory, 2. Quality Assessment, 3. Compliance Check, 4. Documentation, 5. Recommendations. Data audit begins with inventory, quality assessment, compliance check, documentation, and recommendations.

Answer

1. Quality Assessment, 2. Inventory, 3. Compliance Check, 4. Documentation, 5. Recommendations

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1. Inventory, 2. Compliance Check, 3. Quality Assessment, 4. Documentation, 5. Recommendations

Answer

1. Inventory, 2. Quality Assessment, 3. Documentation, 4. Compliance Check, 5. Recommendations

Question 5

A healthcare data analyst is presenting findings on patient readmission rates to a group of hospital administrators. The analysis reveals a 15% increase in readmissions over the past quarter for patients aged 65+ from a specific zip code. However, the administrators are skeptical because previous quarterly reports showed no such trend, and they suspect data quality issues. The analyst must communicate this insight effectively while maintaining credibility. Which of the following approaches should the analyst take?

Accepted Answer

Acknowledge the discrepancy and explain possible reasons such as changes in data collection methods or patient population. It demonstrates the core competency of 'Communicating Data Insights' by acknowledging the discrepancy between the current finding and previous reports, which builds trust with skeptical stakeholders. By explaining possible reasons such as changes in data collection methods or patient population, the analyst maintains credibility and invites collaborative investigation into data quality issues, rather than dismissing concerns or hiding details.

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Emphasize the statistical significance of the finding and ignore previous reports

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Present the data without any explanation and let them draw conclusions

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Remove the demographic detail to avoid controversy

Question 6

A data analyst is creating a dashboard in Looker Studio and needs to combine data from two different data sources using a common field. Which feature should be used?

Accepted Answer

Data blending. Data blending in Looker Studio allows you to combine data from multiple data sources into a single chart or table by joining them on a common dimension (key field). This is the correct feature when you need to merge data from two different sources, such as Google Analytics and Google Sheets, using a shared field like date or campaign ID.

Answer

Community connector

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Filter

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Calculated field

Question 7

An IT operations team monitors 200 servers. Each server reports CPU utilization (0-100%) every five minutes for the past year. The team wants to visualize the data to identify servers that are consistently over 80% utilization and detect any unusual spikes. They have a large dataset with 100,000+ records per server. The current visualization is a single scatter plot with CPU utilization on the y-axis, time on the x-axis, and each server as a different colored point. The chart is extremely cluttered, with points overlapping and colors indistinguishable. What should the team do to improve the visualization?

Accepted Answer

Use a heatmap showing CPU utilization over time per server, or create small multiple charts (one per server). With 200 servers and 100,000+ records per server, a single scatter plot is too cluttered. A heatmap can show CPU utilization over time per server using color intensity, or small multiples (one chart per server) can separate the data. Both approaches reduce overlap and make patterns like consistent over-80% utilization and spikes visible.

Answer

Switch to a line chart with each server as a separate line

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Add a trend line to each server's data and remove the individual points

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Increase the size of the data points to make them more visible

Question 8

A healthcare analytics team is analyzing patient readmission rates. They have a dataset with thousands of records including patient age, diagnosis, length of stay, number of prior admissions, and discharge date. The goal is to identify key factors influencing readmission and create a model to predict high-risk patients. The data is imbalanced: only 5% of patients are readmitted within 30 days. The team plans to use logistic regression. What is the most appropriate approach?

Accepted Answer

Apply oversampling techniques like SMOTE to the training set. With imbalanced data, logistic regression can be biased toward the majority class. Oversampling the minority class (e.g., SMOTE) helps the model learn patterns for readmission. Using accuracy as a metric would be misleading. Removing majority samples discards valuable data. Using data as-is often fails to predict the minority class.

Answer

Use the dataset as is because logistic regression handles imbalance

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Remove most of the non-readmitted patients to balance the dataset

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Use accuracy as the evaluation metric

Question 9

A data analyst wants to show the relationship between advertising spend and sales revenue for 50 stores. Which chart type is most appropriate?

Accepted Answer

Scatter plot. A scatter plot is the most appropriate chart for showing the relationship between two continuous variables—advertising spend and sales revenue—across 50 stores. Each point on the plot represents one store, allowing the analyst to visually assess correlation, trends, or outliers. This aligns with the DA0-001 objective of selecting visualizations that best represent bivariate relationships.

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Line chart

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Bar chart

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Pie chart

Question 10

A company is designing a database for an e-commerce application that requires high transaction throughput and must guarantee that each transaction is processed atomically. Which property of ACID ensures that a transaction is either fully completed or not executed at all?

Accepted Answer

Atomicity. Atomicity is the ACID property that guarantees a transaction is treated as a single indivisible unit — either all of its operations commit or none of them do. If any statement in the transaction fails, the entire transaction is rolled back, leaving the database in its pre-transaction state. This is the 'all-or-nothing' guarantee that the question describes.

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Isolation

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Durability

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Consistency