DA0-002 Practice Test 25 — 15 Questions

Question 1

A data analyst is asked to compare the average sales across three different store locations. The data is normally distributed and variances are approximately equal. Which statistical test is most appropriate?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

ANOVA. ANOVA is used to compare means of three or more groups when assumptions of normality and equal variance are met.

Answer

Pearson correlation

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Chi-square test

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Two-sample t-test

Question 2

Which statistical test should be used to determine if there is a significant association between two categorical variables, such as gender and product preference?

Accepted Answer

Chi-square test. The chi-square test of independence is used to test association between two categorical variables.

Answer

ANOVA

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Pearson correlation

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t-test

Question 3

A data analyst calculates the mean, median, and mode of a dataset. Which of the following measures of central tendency is least affected by extreme outliers?

Accepted Answer

Median. The median is resistant to outliers because it is the middle value, whereas the mean is pulled by extreme values and the mode may not be affected but is less robust for continuous data.

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Range

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Mode

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Mean

Question 4

A data analyst is conducting an A/B test on a website's landing page. The null hypothesis is that there is no difference in conversion rates between the control and treatment groups. After collecting data, the analyst calculates a p-value of 0.03. Using a significance level of α = 0.05, what is the correct conclusion?

Accepted Answer

Reject the null hypothesis; the treatment group has a higher conversion rate.. Since p < α, the null hypothesis is rejected, indicating a statistically significant difference in conversion rates.

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Accept the null hypothesis; the difference is due to chance.

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Fail to reject the null hypothesis; there is no evidence of a difference.

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The result is inconclusive because the p-value is close to 0.05.

Question 5

A data analyst is designing a dashboard for executives. Which TWO practices improve dashboard effectiveness? (Select two.)

Accepted Answer

Including clear labels and titles for all charts. Clear labels and titles help interpretation; consistent color coding aids quick comprehension.

Answer

Adding decorative images to make the dashboard visually appealing

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Displaying data with high precision (e.g., 4 decimal places)

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Using many different colors to highlight every data point

Question 6

A retail company analyzes customer purchase data to improve inventory management. They store daily transaction records in a relational database and monthly aggregate reports in a data warehouse. Which difference between these storage methods best explains why the warehouse is more suitable for trend analysis?

Accepted Answer

The database is optimized for write-heavy OLTP, while the warehouse is optimized for read-heavy OLAP.. OLTP databases are optimized for high-frequency write operations (INSERT/UPDATE/DELETE) and ACID compliance, making them ideal for transaction processing but poor for complex analytical queries. In contrast, a data warehouse is optimized for read-heavy OLAP workloads, using columnar storage, pre-aggregated tables, and indexing strategies that enable fast aggregation and trend analysis over large historical datasets. This architectural difference directly supports the retail company's need to analyze purchase trends over time.

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The database uses a star schema while the warehouse uses a normalized schema.

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The database enforces ACID transactions, while the warehouse uses eventual consistency.

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The database stores only current data, while the warehouse stores historical data.

Question 7

A company is acquiring social media data via a public API. Which TWO considerations are important for ensuring ethical and legal compliance?

Accepted Answer

Anonymize personal identifiable information (PII) before storage. Anonymizing PII before storage is a fundamental data privacy requirement under regulations like GDPR and CCPA. When acquiring data via a public API, the company must ensure that personal identifiers (e.g., names, email addresses, IP addresses) are removed or obfuscated to prevent re-identification, reducing legal liability and ethical risk.

Answer

Share raw data with third parties for additional insights

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Use the data for any internal analysis without restrictions

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Cache data indefinitely to avoid repeated API calls

Question 8

Which TWO roles are primarily responsible for defining and enforcing data governance policies within an organization?

Accepted Answer

Data steward. (Data steward) is correct because data stewards are responsible for the day-to-day management, quality, and enforcement of data governance policies, including data classification, access controls, and compliance with regulatory standards. Option E (Data owner) is correct because data owners are senior stakeholders who define the governance policies, approve data access decisions, and are accountable for the data assets within their domain.

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Data analyst

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Data architect

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Data custodian

Question 9

A data analyst receives the above JSON snippet from a web API. The analyst needs to extract the email addresses for all customers. Which JSONPath expression should be used?

Accepted Answer

$.customers[*].email. The JSONPath expression `$.customers[*].email` uses the wildcard `[*]` to select all elements in the `customers` array and then accesses the `email` property of each element. This matches the requirement to extract email addresses for all customers from the JSON snippet.

Answer

$.customers[0].email

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$..email

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$.customers.email

Question 10

A data scientist is cleaning a dataset and notices missing values in several columns. Which THREE techniques are appropriate for handling missing data? (Select THREE.)

Accepted Answer

Replace missing values with the mean or median. Replacing missing values with the mean (for normally distributed data) or median (for skewed data) is a standard imputation technique that preserves the central tendency of the dataset without introducing bias. This method is appropriate when the missingness is random and the proportion of missing data is low, as it maintains the sample size for analysis.

Answer

Ignore missing values and proceed with analysis

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Always replace missing values with zero

Question 11

A mid-sized e-commerce company stores customer data in a relational database. The database has a table named 'Customers' with columns: CustomerID (primary key), FirstName, LastName, Email, Phone, Address, City, State, ZipCode, and SignUpDate. The company is migrating to a new CRM system that requires a denormalized structure for performance reasons. The new system expects a single table 'CustomerDetails' with columns: CustomerID, FullName (concatenation of first and last name), ContactInfo (JSON object containing email, phone, and address), SignUpDate, and Region (derived from state). The data analyst must design an ETL process to transform the data. During a test run, the analyst notices that some records have missing Phone or Address values. Which of the following is the best approach to handle missing data in the ContactInfo JSON object?

Accepted Answer

Include the missing fields as null in the JSON object.. Representing missing fields as null in the JSON object preserves the data structure and allows downstream systems to explicitly handle null values. This approach maintains data integrity without discarding records or introducing ambiguous placeholder strings that could be misinterpreted as actual data.

Answer

Exclude any record with missing Phone or Address from the migration.

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Set missing values to an empty string in the JSON object.

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Replace missing values with 'N/A' string.

Question 12

A data analyst is cleaning a dataset and finds that 5% of values in the 'income' column are missing. The analyst decides to impute missing values using the mean of the non-missing values. Which potential issue should the analyst be most concerned about?

Accepted Answer

The imputation may reduce the variance and distort the distribution.. Mean imputation reduces variance and can distort relationships, especially if data is skewed. It may also bias estimates if missingness is not random.

Answer

The imputation is not valid because the missing rate is too low.

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The imputation will increase the standard deviation of the variable.

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The imputation will create outliers.

Question 13

Which TWO of the following are primary benefits of implementing a data governance program?

Accepted Answer

Improved data quality and consistency. A primary benefit of a data governance program is improved data quality and consistency. Data governance establishes policies, standards, and procedures for data management, ensuring that data is accurate, complete, and reliable across the organization. This directly enhances decision-making and operational efficiency by reducing errors and inconsistencies in data assets.

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Faster data processing speed

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Increased data volume

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Lower storage costs

Question 14

A data analyst wants to segment customers into groups based on their purchasing behavior. The dataset includes numerical features such as annual income and purchase frequency. Which algorithm is most appropriate for this task?

Accepted Answer

K-means clustering. K-means clustering is a common algorithm for customer segmentation based on numerical features.

Answer

Linear regression

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Logistic regression

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Chi-square test

Question 15

A data analyst is testing whether a new website layout increases conversion rate. The p-value from the test is 0.03. Using a significance level of 0.05, what is the correct conclusion?

Accepted Answer

Reject the null hypothesis; the new layout significantly increases conversion rate. Since p-value (0.03) < α (0.05), we reject the null hypothesis and conclude there is a statistically significant difference.

Answer

The test is inconclusive because p-value is greater than 0.01

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Accept the null hypothesis; the new layout has no effect

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Fail to reject the null hypothesis; the new layout does not increase conversion rate