DA0-002 Practice Test 4 — 25 Questions

Question 1

A data team must implement a data retention policy to reduce storage costs while meeting legal requirements. Which TWO actions best achieve this?

Accepted Answer

Set data retention limits with automated deletion. Option A is correct because setting data retention limits with automated deletion enforces the legal retention policy by removing data once its required retention period expires, directly reducing stored volume and storage costs. Option E is correct because archiving historical data to tape or cloud archive tiers moves infrequently accessed data to much cheaper storage media while still preserving it for legal and compliance requirements. Together, these two actions address both cost reduction and legal retention. Option B (data compression) reduces the size of stored data but does not enforce retention or remove data that has exceeded its legal retention period. Option C (increasing primary storage capacity) raises costs rather than reducing them and does nothing to meet retention requirements. Option D (data deduplication) eliminates redundant copies but does not implement a retention policy or remove expired data.

Answer

Use data compression

Answer

Increase primary storage capacity

Answer

Implement data deduplication

Question 2

A university database stores student information in a normalized schema. The 'students' table has a primary key 'student_id'. The 'enrollments' table has a foreign key 'student_id' referencing 'students'. Which two of the following are true about primary and foreign keys? (Select TWO)

Accepted Answer

A foreign key ensures referential integrity between tables. A foreign key enforces referential integrity by ensuring that every value in the foreign key column of the 'enrollments' table matches a valid primary key value in the 'students' table. This prevents orphaned records and maintains consistency across related tables in a normalized relational database.

Answer

A foreign key must have the same name as the primary key it references

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A foreign key can reference a column that is not a primary key

Answer

A table can have multiple primary keys

Question 3

A data analyst calculates the mean, median, and mode of a dataset. Which of the following best describes how these measures are used in descriptive statistics?

Accepted Answer

To describe the central tendency of the data. Mean, median, and mode are measures of central tendency, which are used in descriptive statistics to summarize the center point of a dataset. They describe where the data tends to cluster. The correct answer is C because these measures describe the central tendency.

Answer

To identify outliers using standard deviation

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To test hypotheses about population parameters

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To determine the probability of an event

Question 4

A data analyst wants to show the proportion of total sales for each product category. There are 4 categories. Which chart type is most appropriate?

Accepted Answer

Pie chart. A pie chart is designed to show parts of a whole, making it the most appropriate choice for displaying the proportion of total sales contributed by each of four product categories. With only four categories, the slices remain readable and the proportional relationship is immediately clear. Pie charts work best when the number of categories is small (typically 5 or fewer) and the values sum to a meaningful total.

Answer

Line chart

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Scatter plot

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Histogram

Question 5

An analyst creates a histogram of customer transaction amounts but observes that the distribution looks bimodal. Upon review, the analyst realizes that two different customer segments (retail and wholesale) were combined. Which action best addresses this?

Accepted Answer

Create two separate histograms, one for each segment. Creating two separate histograms, one for each customer segment (retail and wholesale), best addresses the bimodal distribution because it allows the analyst to see the underlying distributions of each segment clearly. Combining them into one histogram obscures the distinct patterns, while separating them reveals the true characteristics of each group. This is a fundamental principle of data visualization: when data contains subgroups, disaggregating can provide more meaningful insights.

Answer

Use a single histogram with two colors for segments

Answer

Use a box plot instead of a histogram

Answer

Increase the number of bins to see more detail

Question 6

A data analyst is creating a dashboard in Looker Studio for an e-commerce company. They want to display the average order value by product category, and also allow users to filter by date range. Which combination of elements should be used?

Accepted Answer

Dimension: Product Category; Metric: Average Order Value; Control: Date Range. In Looker Studio, the field you group by is the dimension and the field you aggregate is the metric. To show average order value by product category, Product Category must be the dimension and Average Order Value the metric, with a Date Range control added for user filtering. This is the only option that assigns the roles correctly and includes the required control.

Answer

Dimension: Order Value; Metric: Product Category; Control: Date Range

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Dimension: Date; Metric: Product Category; Control: None

Answer

Dimension: Average Order Value; Metric: Product Category; Control: Date Range

Question 7

Refer to the exhibit. A database administrator notices that queries filtering on both CustomerID and OrderDate are slow. Which single change would most likely improve performance for such queries?

Accepted Answer

Add a composite index on (CustomerID, OrderDate). A composite index on (CustomerID, OrderDate) allows the database to satisfy queries that filter on both columns using a single index seek, avoiding a full table scan or multiple index lookups. The column order matters: CustomerID first supports equality filtering, and OrderDate second supports range or sort operations within each customer. This is the most direct performance improvement for the described query pattern.

Answer

Partition the table by OrderDate

Answer

Convert TotalAmount to VARCHAR

Answer

Remove the primary key constraint

Question 8

In simple linear regression, the coefficient of determination R² measures:

Accepted Answer

The proportion of variance in the dependent variable explained by the independent variable. R², the coefficient of determination, quantifies the proportion of variance in the dependent variable that is explained by the independent variable(s) in the regression model. It ranges from 0 to 1, where 1 means the model explains all variance and 0 means it explains none.

Answer

The probability that the slope is zero

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The slope of the regression line

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The strength and direction of the linear relationship

Question 9

In a regression analysis, the coefficient of determination (R²) is 0.85. How should this value be interpreted?

Accepted Answer

85% of the variance in the dependent variable is explained by the model. R², the coefficient of determination, measures the proportion of variance in the dependent variable that is explained by the independent variables in the regression model. An R² of 0.85 means 85% of the variance in the dependent variable is accounted for by the model, indicating a strong fit.

Answer

85% of the data points lie on the regression line

Answer

The slope of the regression line is 0.85

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85% of the independent variables are significant

Question 10

A data analyst wants to compare the sales revenue of five different product categories for the current month. Which chart type is most suitable for this comparison?

Accepted Answer

Bar chart. A bar chart encodes each product category as a discrete bar whose length maps to revenue, making side-by-side comparison of five categorical values immediate and precise. Categorical comparisons are the canonical use case for bar charts because the human eye judges length differences far more accurately than angles or slopes.

Answer

Histogram

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Pie chart

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Line chart

Question 11

A data analyst is creating a presentation for executives to explain why customer churn has increased over the last quarter. The analyst wants to present the story in a compelling way. Which narrative structure is most appropriate?

Accepted Answer

Situation, Complication, Resolution. The Situation-Complication-Resolution structure is ideal for executive presentations because it first establishes the context (situation), then introduces the problem (complication—increased churn), and finally proposes a solution (resolution). This narrative arc aligns with how executives process strategic issues, making the data story compelling and actionable. In contrast, other structures are better suited for technical reports or hypothesis testing, not high-level storytelling.

Answer

Problem, Hypothesis, Test

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Background, Analysis, Recommendation

Answer

Data, Visualization, Conclusion

Question 12

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

Accepted Answer

Mean. The mean is sensitive to extreme values because it includes all data points in its calculation, whereas median and mode are more robust.

Answer

Range

Answer

Median

Answer

Mode

Question 13

A data governance team is establishing policies to ensure data quality. They define rules for data accuracy, completeness, and consistency. Which data governance function is primarily responsible for defining and enforcing these rules?

Accepted Answer

Data quality management. Data quality management is the governance function specifically responsible for defining data quality dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness) and implementing the rules, profiling, and monitoring to enforce them. It translates governance policy into measurable quality controls and remediation workflows.

Answer

Data stewardship

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Data ownership

Answer

Master data management

Question 14

A data analyst is performing data acquisition from multiple source files. Which TWO data profiling tasks should the analyst complete before loading the data into the target system?

Accepted Answer

Verify data types and formats. Option B (Verify data types and formats) is correct because data profiling must confirm that each source column's actual data type (e.g., integer, string, date) and format (e.g., YYYY-MM-DD, decimal separators) match what the target system expects, preventing load failures or silent corruption. Option E (Identify missing values and nulls) is correct because profiling must detect NULLs, empty strings, and placeholder values so the analyst can decide on imputation, defaulting, or rejection rules before loading. Option A (Create a dashboard for stakeholders) is a downstream reporting activity, not a pre-load profiling task. Option C (Build a linear regression model) is predictive analytics performed after data is cleansed and loaded, not profiling. Option D (Perform cluster analysis) is an unsupervised modeling technique also done post-load, so it does not belong in pre-load data profiling.

Answer

Create a dashboard for stakeholders

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Build a linear regression model

Answer

Perform cluster analysis

Question 15

A data analyst needs to visualize the distribution of customer ages in a dataset containing 10,000 records. The analyst wants to see the shape of the distribution and identify any outliers. Which chart type is most appropriate?

Accepted Answer

Histogram. A histogram is most appropriate because it displays the full shape of a continuous distribution (e.g., normal, skewed, bimodal) across bins, and the tails of the histogram make extreme values visually apparent. With 10,000 records, binning ages reveals both the overall distribution shape and where outliers fall at the extremes. Box plots also show outliers, but they compress the distribution into five summary statistics and hide the shape.

Answer

Line chart

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Box plot

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Pie chart

Question 16

A marketing team wants to explore the relationship between advertising spend (in dollars) and resulting revenue. Which chart type is most suitable?

Accepted Answer

Scatter plot. A scatter plot is designed to display the relationship between two quantitative variables, with one variable on the x-axis and the other on the y-axis. Plotting advertising spend against revenue allows the marketing team to visually assess correlation, trends, and outliers. This is the standard chart type for bivariate numerical analysis.

Answer

Line chart

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Table

Answer

Pie chart

Question 17

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. Option C is correct because a highly knowledgeable audience of data scientists can evaluate and trust the analysis when the presenter includes the technical details and methodology, such as the statistical tests, model choices, and parameter settings used. Option D is correct because presenting the assumptions and limitations of the analysis is essential for a technical audience to properly interpret the results, assess validity, and understand the boundaries of the conclusions. Options A, B, and E are not appropriate: hiding uncertainty undermines scientific integrity, basic visualizations like pie charts are inadequate for complex statistical findings, and oversimplifying would frustrate or mislead an expert audience rather than clarify the analysis.

Answer

Avoid mentioning uncertainty to maintain confidence

Answer

Use basic visualizations like pie charts

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Simplify the findings to avoid confusion

Question 18

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 19

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

Answer

$.customers.email

Question 20

In a table 'sales_team' with columns 'salesperson', 'quarter', and 'revenue', an analyst wants to assign a rank to each salesperson within their quarter based on revenue, with the highest revenue getting rank 1. However, if two salespeople have the same revenue, they should receive the same rank, and the next rank should be the next consecutive integer (no gaps). Which window function should be used?

Accepted Answer

DENSE_RANK(). DENSE_RANK() assigns ranks without gaps, so if two salespeople tie for rank 1, the next rank is 2. This matches the requirement that ties receive the same rank and the next rank is consecutive. It is the correct window function for this scenario.

Answer

RANK()

Answer

NTILE(4)

Answer

ROW_NUMBER()