DA0-002 Practice Test 2 — 30 Questions

Question 1

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. Placing the most important KPIs in the top-left corner follows natural reading patterns (left-to-right, top-to-bottom), ensuring executives see critical metrics first. Option A is wrong because including too many charts on a single screen reduces readability and can overwhelm users. Option B is wrong because hiding KPIs behind filters defeats the purpose of having them visible at a glance. Option C is wrong because using distinct colors for all KPIs equally does not prioritize information; it may actually create visual clutter and reduce clarity.

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 2

A data analyst wants to generate a report showing employee names and their department names, but some employees are not assigned to any department. The analyst wants to include all employees. Which JOIN type should be used?

Accepted Answer

LEFT JOIN. LEFT JOIN includes all rows from the left table (employees) even if no match in departments.

Answer

INNER JOIN

Answer

CROSS JOIN

Answer

RIGHT JOIN

Question 3

A data analyst needs to extract the year from a column named 'order_date' in a SQL database. The database supports standard SQL functions. Which function should they use?

Accepted Answer

EXTRACT(YEAR FROM order_date). The EXTRACT function is standard SQL for extracting date parts. EXTRACT(YEAR FROM order_date) returns the year.

Answer

GET_YEAR(order_date)

Answer

YEAR(order_date)

Answer

DATE_PART('year', order_date)

Question 4

A data analyst creates a dashboard that includes a map showing sales by region. The map uses a continuous color gradient from light yellow to dark blue. Some regions with very high sales appear as dark blue, but many regions with moderate sales appear similar. Which improvement would most enhance the readability?

Accepted Answer

Use a discrete color scale with distinct bins for sales ranges.. A discrete color scale with distinct bins for sales ranges eliminates the ambiguity caused by a continuous gradient, where moderate sales values blend together. By grouping sales into defined intervals (e.g., $0–$10K, $10K–$50K, etc.), each region is assigned a unique, easily distinguishable color, making it immediately clear which sales bracket a region falls into without requiring precise color differentiation.

Answer

Switch to a diverging color scheme with a neutral midpoint.

Answer

Increase the map size to show more detail.

Answer

Add data labels to each region showing exact sales numbers.

Question 5

In a logistic regression model predicting customer churn (1 = churn, 0 = not churn), the coefficient for 'contract length' is -0.5. Which of the following is the correct interpretation?

Accepted Answer

For each unit increase in contract length, the log-odds of churn decrease by 0.5.. In logistic regression, coefficients represent the log-odds change. A negative coefficient decreases the log-odds, meaning lower probability of churn.

Answer

Longer contract length increases the odds of churn.

Answer

The probability of churn decreases by 50% for each unit increase in contract length.

Answer

Contract length is not a significant predictor.

Question 6

A retail company has a dashboard that tracks daily sales across all stores. The dashboard is used by the CEO during monthly board meetings. Recently, the CEO complained that the dashboard is confusing and takes too long to interpret. The data analyst is asked to redesign the dashboard to improve usability. The analyst has access to all sales data. The CEO prefers a high-level overview with the ability to drill down into regions if needed. The analyst must decide on a course of action. What should the analyst do first?

Accepted Answer

Interview the CEO to determine key performance indicators and preferred layout.. The correct first step is to interview the CEO to determine key performance indicators and preferred layout. This ensures the dashboard is designed around the specific high-level metrics the CEO needs for monthly board meetings, with the ability to drill down into regions. Starting with stakeholder requirements prevents wasted effort on irrelevant visualizations or formats.

Answer

Revamp the dashboard with as many visualizations as possible.

Answer

Conduct a survey of all employees to understand their needs.

Answer

Create a static PDF report instead of a dashboard.

Question 7

A data engineer is designing an ETL pipeline to extract sales data from a legacy on-premise database and load it into a cloud data warehouse. The database is slow and queries during business hours affect performance. Which extraction strategy minimizes impact?

Accepted Answer

Incremental extraction using Change Data Capture (CDC). Incremental extraction using Change Data Capture (CDC) minimizes impact on the legacy on-premise database by reading only the changed rows (inserts, updates, deletes) from transaction logs or change tables, rather than issuing heavy SELECT queries. This avoids full table scans or frequent queries during business hours, preserving database performance for operational workloads.

Answer

Query the database with SELECT * every hour

Answer

Full table extraction nightly

Answer

Use a database log shipping

Question 8

Which TWO of the following are examples of supervised learning algorithms?

Accepted Answer

Linear regression. Linear regression is a supervised learning algorithm because it learns a mapping from input features to a continuous target variable using labeled training data. The model minimizes the difference between predicted and actual values (e.g., via ordinary least squares) to make predictions on new data.

Answer

K-means clustering

Answer

Principal component analysis (PCA)

Answer

Apriori algorithm

Question 9

Which THREE of the following are assumptions of linear regression? (Select THREE).

Accepted Answer

Independence of errors. Independence of errors is a core assumption of linear regression, meaning the residuals (errors) should not be correlated with each other. This is critical for valid inference because correlated errors violate the Gauss-Markov theorem, leading to biased standard errors and unreliable hypothesis tests. In time series data, this assumption is often violated due to autocorrelation, which can be detected using the Durbin-Watson test.

Answer

Normal distribution of independent variables

Answer

Multicollinearity among independent variables

Question 10

A data analyst frequently receives ad hoc requests for the same type of analysis. Which TWO approaches could reduce the number of ad hoc requests?

Accepted Answer

Create a scheduled report that covers the common analysis. Building self-service capabilities and iterating on feedback to improve scheduled reports can address recurring needs and reduce ad hoc requests.

Answer

Increase data freshness to real-time

Answer

Add more security to the data

Answer

Ignore the requests until they become urgent

Question 11

A data analyst is creating a self-service reporting environment. Which data governance practice ensures users see only data relevant to their department?

Accepted Answer

Row-level security. Row-level security restricts data access based on user roles, ensuring users only see authorized data.

Answer

Data lineage

Answer

Data dictionary

Answer

Single version of truth

Question 12

Which TWO are common pitfalls when communicating data insights?

Accepted Answer

Using misleading scales on charts. 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.

Answer

Explaining assumptions clearly

Answer

Including a clear call to action

Answer

Providing context for the data

Question 13

A data analyst is examining the relationship between advertising spend (in dollars) and revenue (in dollars). The Pearson correlation coefficient r is calculated as +0.92. Which of the following interpretations is correct?

Accepted Answer

There is a strong positive linear relationship.. r = +0.92 indicates a strong positive linear relationship.

Answer

There is a strong negative linear relationship.

Answer

There is no linear relationship.

Answer

92% of the variation in revenue is explained by advertising spend.

Question 14

A data analyst is performing exploratory data analysis on a dataset containing house prices. They want to identify outliers in the 'price' column using the IQR method. The first quartile (Q1) is $200,000, the third quartile (Q3) is $350,000, and the IQR is $150,000. What is the upper bound for identifying outliers?

Accepted Answer

$575,000. The IQR method defines outliers as values below Q1 - 1.5*IQR or above Q3 + 1.5*IQR. Upper bound = 350,000 + (1.5 * 150,000) = 350,000 + 225,000 = $575,000.

Answer

$500,000

Answer

$425,000

Answer

$650,000

Question 15

A healthcare analytics team is responsible for producing a monthly dashboard for hospital administrators. The dashboard includes key metrics such as patient admission rates, average length of stay, readmission rates, and bed occupancy. For the current month, the data shows a significant increase in average length of stay. The data analyst suspects that this increase is due to a new chronic disease management program that was implemented at the beginning of the month. However, the analyst also notices that the data for the previous month had an error: some discharge dates were incorrectly recorded, causing the average length of stay to be artificially low. The analyst needs to communicate the insights to the administrators, who are concerned about the increase. Which of the following is the best course of action?

Accepted Answer

Correct the previous month's data, recalculate the change, and present the increase alongside an explanation of the new program and the data correction.. The best course of action because it addresses both the data quality issue and the business concern. By correcting the previous month's erroneous discharge dates, the analyst recalculates the true baseline, ensuring the reported increase in average length of stay is accurate. Presenting the corrected data alongside an explanation of the new chronic disease management program provides a complete, transparent narrative that separates the impact of the data error from the program's effect, which is essential for informed decision-making by hospital administrators.

Answer

Correct the previous month's data and present the adjusted increase, emphasizing the data error.

Answer

Present the raw data as-is and explain that the increase is due to the new program.

Answer

Delay the report until the next month to gather more data on the program's effect.

Question 16

A data analyst wants to extract the year from a date column 'order_date' in a SQL database. Which function should be used?

Accepted Answer

YEAR(order_date). The YEAR() function extracts the year from a date. DATEADD adds intervals, DATEDIFF calculates differences, GETDATE() returns current date.

Answer

DATEADD(year, order_date, 0)

Answer

DATEDIFF(year, order_date, GETDATE())

Answer

GETDATE()

Question 17

An analyst notices that a dashboard displays conflicting data from two sources. What is the first step in troubleshooting?

Accepted Answer

Check data transformation steps and join logic. The first step in troubleshooting conflicting data from multiple sources is to verify the data transformation steps and join logic. Conflicts often arise from incorrect joins (e.g., using INNER JOIN instead of LEFT JOIN), mismatched keys, or data type conversions that alter values. Checking these steps isolates the root cause before any other action, such as re-running queries or notifying stakeholders.

Answer

Re-run all queries

Answer

Notify stakeholders of potential error

Answer

Replace the data source with the one believed to be correct

Question 18

Based on the exhibit, what is the most likely cause of the import failure?

Accepted Answer

A data quality issue: the date field contains an invalid date.. The exhibit shows a date field containing '2023-02-30', which is an invalid date (February never has 30 days). This data quality issue causes the import to fail, as the system likely validates date values against calendar rules before inserting them into the target table. The error is not due to file emptiness, non-numeric characters, or corruption, but specifically a semantic data integrity violation.

Answer

The file is empty or contains only headers.

Answer

The price field includes non-numeric characters that cannot be parsed.

Answer

The source file is corrupted or in an unsupported format.

Question 19

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.

Answer

Trigger

Answer

Stored procedure

Answer

Index

Question 20

Refer to the exhibit. What data quality issue is indicated?

Accepted Answer

Non-standardized data entry. The error shows that a non-numeric value 'N/A' is present in a numeric column, indicating non-standardized data entry. Duplication, inconsistency, or outliers are not directly shown.

Answer

Data inconsistency

Answer

Outlier

Answer

Data duplication