DA0-002 Practice Test 36 — 15 Questions

Question 1

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

Answer

Share raw data tables

Answer

Use detailed statistical jargon

Question 2

An e-commerce company wants to provide real-time personalized product recommendations based on customer browsing behavior. Currently, they have a traditional data warehouse that processes batch updates every night. The marketing team complains that recommendations are outdated within hours because customers see yesterday's data. The data engineer needs to modify the architecture to support near-real-time analytics. The budget is limited, and the existing warehouse infrastructure must be reused as much as possible. Which architectural change would best meet the requirement?

Accepted Answer

Implement a streaming data pipeline (e.g., Apache Kafka) that feeds a real-time recommendation engine.. Implementing a streaming data pipeline like Apache Kafka enables the ingestion and processing of customer browsing events in near real-time, feeding a dedicated recommendation engine that can update recommendations within seconds or minutes. This approach reuses the existing data warehouse for historical analytics and batch reporting while adding a lightweight streaming layer for low-latency recommendations, aligning with the limited budget and reuse requirement.

Answer

Replace the warehouse with an in-memory database for real-time processing.

Answer

Add more nodes to the warehouse cluster to speed up batch processing.

Answer

Increase the frequency of batch load from nightly to every hour.

Question 3

A data analyst is cleaning a dataset and finds that a numeric field has several missing values. The variable is normally distributed. Which imputation method is most appropriate?

Accepted Answer

Mean imputation. For normally distributed data, mean imputation is common and preserves the mean.

Answer

Median imputation

Answer

Mode imputation

Answer

Forward-fill

Question 4

A data analyst is reviewing a data lake access policy that controls access to a data lake. The analyst wants to communicate that the current policy restricts data downloads to a specific IP range. Which of the following best describes the policy's effect?

Accepted Answer

The policy restricts data downloads to a specific IP range.. The access policy explicitly restricts data downloads to a specific IP range by using a condition in the policy statement, such as a source IP address with a CIDR block. This means only requests originating from IP addresses within that range are allowed to perform the download action, effectively limiting downloads to authorized network locations.

Answer

The policy allows all users to download data.

Answer

The policy denies data downloads to all users.

Answer

The policy allows data uploads from a specific IP range.

Question 5

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

Answer

Background, Analysis, Recommendation

Answer

Data, Visualization, Conclusion

Question 6

A company ingests customer clickstream data from its website. The data arrives continuously in JSON format and must be stored for real-time analytics. Which type of data source is being described?

Accepted Answer

Streaming data. The description matches a streaming data source because clickstream data arrives continuously in JSON format and must be stored for real-time analytics. Streaming data sources, such as Apache Kafka or Amazon Kinesis, ingest unbounded data in real time, enabling immediate processing and analytics without batch delays.

Answer

Transactional database

Answer

Flat file

Answer

Data warehouse

Question 7

Refer to the exhibit. A data analyst is trying to understand access permissions for the company data folder. Which statement accurately describes the effective permissions?

Accepted Answer

DataAnalyst can read objects in the production folder except those in the sensitive subfolder.. The exhibit shows an access control policy that grants the DataAnalyst user read permission on the production folder, but includes an explicit deny rule for the sensitive subfolder specified via a path condition. In most access control systems, explicit deny rules take precedence over allow rules, so the deny on the sensitive subfolder overrides the allow on the production folder, effectively blocking read access to objects in the sensitive subfolder while permitting reads elsewhere in the production folder.

Answer

DataAnalyst can read all objects in the production folder, including the sensitive subfolder.

Answer

No one can read from the production folder except DataAnalyst.

Answer

Only DataAnalyst is allowed to read from the entire production folder.

Question 8

An analyst needs to retrieve the year from an order_date column (datetime type). Which function should be used in SQL?

Accepted Answer

EXTRACT(YEAR FROM order_date). EXTRACT(YEAR FROM order_date) is the standard SQL function to get the year part.

Answer

FORMAT(order_date, 'yyyy')

Answer

DATEADD(YEAR, order_date, 0)

Answer

YEAR(order_date)

Question 9

A retail analyst wants to visualize monthly sales over the past year to identify seasonal patterns. Which chart type is best?

Accepted Answer

Line chart. A line chart is best for visualizing monthly sales over time because it explicitly shows trends and seasonal patterns across a continuous time axis. The sequential ordering of months allows the line to connect data points, making it easy to identify peaks, troughs, and recurring cycles. This aligns with the DA0-001 objective of selecting appropriate visualizations for time-series data.

Answer

Pie chart

Answer

Histogram

Answer

Box plot

Question 10

Which TWO of the following are common assumptions of linear regression?

Accepted Answer

Independence of observations. Linear regression relies on several assumptions for valid OLS estimation. Two fundamental assumptions are independence of observations (option A), meaning the residuals are independent, and linearity of the relationship (option C), meaning the model correctly specifies a linear relationship between predictors and outcome. While homoscedasticity (equal variance of residuals) is also an important assumption, it is not listed as one of the two most common assumptions in this context. Options B and D are incorrect: no multicollinearity applies only to multiple regression, and normality of the dependent variable is not required; rather, normality of residuals is needed for hypothesis testing.

Answer

No multicollinearity

Answer

Normality of the dependent variable

Answer

Homoscedasticity

Question 11

Which TWO of the following are best practices when creating a data visualization for a presentation to stakeholders?

Accepted Answer

Including interactive filters when possible to allow stakeholders to explore data. Interactive filters (e.g., slicers, parameter controls) empower stakeholders to drill down into specific data subsets, ask ad-hoc questions, and uncover insights without overwhelming the initial view. This aligns with the principle of user-driven exploration, which is a best practice for stakeholder presentations where different audience members may have varying interests. Including interactivity also reduces the need for multiple static charts, keeping the presentation concise while still offering depth.

Answer

Placing the legend at the bottom of the chart

Answer

Using 3D effects to make the chart visually appealing

Answer

Using only one type of chart throughout the presentation for consistency

Question 12

A data analyst is designing a database for a retail application. Which TWO of the following are valid reasons to use a NoSQL document database like MongoDB instead of a relational database? (Select 2)

Accepted Answer

The data structure evolves frequently. NoSQL document databases like MongoDB are schema-flexible, allowing the data structure to evolve over time without requiring migrations or downtime. This is ideal for agile development where application requirements change frequently, as documents can have varying fields without breaking existing records.

Answer

The application requires high-speed transactional consistency

Answer

The data has a fixed schema with many relationships

Answer

The application needs complex joins across multiple tables

Question 13

A data analyst needs to combine two datasets: one contains customer information (customer_id, name, address) and the other contains order information (order_id, customer_id, order_date). The analyst wants to include all customers, even those who have not placed orders. Which type of join should be used?

Accepted Answer

LEFT JOIN. A LEFT JOIN returns all rows from the left table (customers) and the matching rows from the right table (orders). If a customer has no orders, the order columns will contain NULLs. This satisfies the requirement to include all customers, even those without orders.

Answer

FULL OUTER JOIN

Answer

INNER JOIN

Answer

RIGHT JOIN

Question 14

A dataset contains height measurements in centimeters and inches. An analyst wants to apply k-means clustering. Which data transformation should be applied before clustering?

Accepted Answer

Min-max normalization. Min-max normalization scales features to a range, often [0,1], which is appropriate for distance-based algorithms like k-means.

Answer

Log transformation

Answer

Z-score standardization

Answer

No transformation needed

Question 15

Refer to the exhibit. What does the query return?

Accepted Answer

Customers who have placed more than 5 orders.. The query uses a HAVING clause with COUNT(*) > 5, which filters groups (by customer ID) to only those with more than 5 orders. The GROUP BY customer ID ensures the count is per customer, so the result is customers who have placed more than 5 orders. Option C is correct because the condition is strictly greater than 5, not at least 5.

Answer

All orders grouped by customer ID.

Answer

Customers who have placed at least 5 orders.

Answer

All customers who have placed orders.