DA0-002 Practice Test 39 — 15 Questions

Question 1

A data analyst is tasked with combining customer data from a CRM system and a billing system. The CRM uses a GUID for customer ID, while billing uses an integer. Which approach should the analyst use to ensure a reliable merge?

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

Accepted Answer

Standardize the customer ID format and use it as the join key.. Standardizing the customer ID format (e.g., converting the billing integer to a GUID or mapping both to a common string key) ensures a consistent join key across heterogeneous systems. This eliminates type mismatch errors and guarantees that each customer record can be matched reliably, as GUIDs are globally unique and integers are typically sequential, so direct comparison would fail without transformation.

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Use the customer name as the join key.

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Merge using a cross-join and then filter manually.

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Perform a fuzzy match on the customer address.

Question 2

A company is migrating its data pipeline from on-premises to the cloud. The current ETL process transforms data before loading into a data warehouse. The new architecture will use ELT instead. Which THREE of the following are advantages of ELT over traditional ETL? (Select 3)

Accepted Answer

Provides ability to reprocess raw data if transformation logic changes. ELT leverages cloud scalability, allows raw data storage for flexibility, and enables schema-on-read.

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Ensures data quality before loading

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Reduces storage costs by storing only transformed data

Question 3

Which TWO of the following are characteristics of structured data? (Choose TWO.)

Accepted Answer

Stored in rows and columns. Structured data is organized into rows and columns, typically within relational databases or spreadsheets, where each column represents a specific attribute and each row represents a record. This tabular format enables efficient querying, sorting, and indexing using languages like SQL. The rigid row-and-column structure ensures data consistency and supports ACID (Atomicity, Consistency, Isolation, Durability) properties.

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Lacks a fixed schema

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Uses tags to define elements

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Consists of free-form text

Question 4

A marketing team wants to collect data on competitor pricing for similar products. Which data source is most appropriate?

Accepted Answer

External public web scraping. External public web scraping is the most appropriate data source because competitor pricing is publicly available on websites, and web scraping allows automated extraction of this structured or unstructured data. This approach directly addresses the need for external competitive intelligence without relying on internal or customer-reported data.

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Customer surveys

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Internal ERP system

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Internal sales data

Question 5

An analyst wants to show the distribution of test scores for 500 students. Which visualization type is best for understanding the shape of the distribution?

Accepted Answer

Histogram. A histogram is the correct choice because it groups continuous test scores into bins and displays the frequency of scores within each bin, allowing the analyst to see the shape of the distribution (e.g., normal, skewed, bimodal). This directly addresses the goal of understanding distribution shape, which is a core use case for histograms in data visualization.

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Line chart

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Pie chart

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Scatter plot

Question 6

A data analyst is creating a data story for a marketing campaign results. Which of the following narrative structures is most effective for engaging the audience?

Accepted Answer

Start with a key insight or finding, then provide supporting evidence.. Starting with a key insight or finding captures the audience's attention immediately, and then providing supporting evidence builds a compelling narrative that keeps the audience engaged. Option A uses a question-and-answer format without a clear flow, which can be confusing and lacks direction. Option B presents all data points chronologically, which may be monotonous and fail to highlight the most important insights. Option C starts with methodology, which is technical and may lose the audience before the key findings are presented.

Answer

Use a question-and-answer format without a clear flow.

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Present all data points chronologically.

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Start with the methodology, then data, then results.

Question 7

A hospital's patient records system must process thousands of small transactions per second. Which type of database system is best suited for this workload?

Accepted Answer

OLTP. OLTP (Online Transaction Processing) systems are designed to handle a high volume of small, concurrent transactions with low latency and high concurrency. This makes them ideal for a hospital patient records system that must process thousands of small transactions per second, such as patient check-ins, prescription updates, and billing entries.

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Data mart

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Data warehouse

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OLAP

Question 8

A healthcare analytics team is building a dashboard to monitor patient vitals. They receive data from two sources: Source 1 provides 'heart rate' as an integer (beats per minute), and Source 2 provides 'blood pressure' as a ratio (systolic/diastolic, e.g., 120/80). The team wants to create a combined metric called 'cardiac stress index' that uses both heart rate and systolic blood pressure. However, they notice that heart rate data occasionally contains negative values due to sensor errors. The data governance policy requires that all data be valid and meaningful. Which action best addresses the data quality issue while preserving the data types?

Accepted Answer

Remove all records with negative heart rate values as they are invalid. Negative heart rate values are physiologically impossible and violate the data governance policy requiring valid and meaningful data. Removing these records ensures the dashboard only contains accurate, actionable data without altering the original integer data type of heart rate, preserving its numerical integrity for the 'cardiac stress index' calculation.

Answer

Convert heart rate to absolute values (remove the negative sign)

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Keep negative values but set them to NULL to indicate missing data

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Change heart rate from integer to categorical (e.g., low, normal, high) to avoid negative issues

Question 9

During a presentation, a stakeholder questions the validity of a correlation found. What is the best response?

Accepted Answer

Correlation does not imply causation, but we can perform further analysis.. It directly addresses the stakeholder's concern about validity by acknowledging the fundamental statistical principle that correlation does not imply causation. It then proposes a constructive next step—further analysis—which aligns with best practices in data communication, where validating insights requires additional testing (e.g., controlled experiments or causal inference methods). This response demonstrates both technical honesty and a commitment to rigorous data-driven decision-making.

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We can accept the correlation as true.

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We used a large sample so it's valid.

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The p-value is low, so it's significant.

Question 10

A researcher is designing an A/B test to compare two website layouts. Which TWO elements are essential for determining the required sample size?

Accepted Answer

Statistical power. Statistical power and desired effect size are key inputs for sample size calculation.

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Sample mean

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Confidence interval width

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P-value

Question 11

A data analyst needs to design a report for two audiences: executives want a high-level trend, and operational managers need current inventory levels. Which approach best satisfies both?

Accepted Answer

Create two separate reports: an executive summary with trends and an operational dashboard with real-time inventory.. Providing a summary view for executives and a detailed view for operational managers addresses different needs.

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Include all details in one report so everyone sees the same information.

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Send only the operational dashboard and let executives derive trends.

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Ask the stakeholders to agree on a single view.

Question 12

Which TWO data types are considered quantitative? (Select two.)

Accepted Answer

Customer satisfaction rating (1-5). Temperature in Celsius is quantitative because it is a continuous numerical measurement on an interval scale, allowing for meaningful arithmetic operations. Customer satisfaction rating (1-5) is also quantitative because the numbers represent a measurable quantity (level of satisfaction) that can be averaged and compared, often treated as interval data in business analytics. The other options are categorical: Product color is nominal, Zip code and Employee ID are nominal identifiers.

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Product color

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Zip code

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Employee ID

Question 13

A data analyst needs to ensure that a customer's address is stored in a consistent format across multiple databases. Which data quality dimension is the analyst primarily concerned with?

Accepted Answer

Consistency. The data analyst is primarily concerned with consistency, which ensures that the same data values are represented uniformly across different systems or databases. In this scenario, the customer's address must follow the same format (e.g., street, city, state, ZIP code) in every database to enable reliable merging and querying. Consistency is a key data quality dimension that focuses on cross-system uniformity, distinct from accuracy (correctness of values) or completeness (presence of all required fields).

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Completeness

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Accuracy

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Timeliness

Question 14

A data analyst creates a heatmap to show website click-through rates by hour and day of week. The heatmap uses a green-to-red gradient, but users cannot distinguish between moderate values. What is the best fix?

Accepted Answer

Switch to a diverging color scheme with a neutral center. A diverging color scheme with a neutral center (e.g., white or light gray) allows users to distinguish moderate values from extremes by providing a clear visual midpoint. The original green-to-red gradient is a sequential scheme that compresses moderate values into a narrow perceptual range, making them indistinguishable. Switching to a diverging palette solves this by mapping moderate values to the neutral center and extremes to the endpoints.

Answer

Remove all but the highest and lowest values

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Add black borders around each cell

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Increase the size of each heatmap cell

Question 15

You are a data analyst for a logistics company. The company has a fleet of delivery trucks and tracks performance metrics including delivery time, fuel consumption, and distance traveled. Management wants a dashboard to monitor driver efficiency and identify underperforming drivers. You have access to a dataset with columns: DriverID, Date, RouteID, Distance (miles), FuelUsed (gallons), DeliveryTime (minutes). The dataset contains 10,000 records from the past year. You need to create a visualization that allows management to quickly compare the average fuel efficiency (miles per gallon) of drivers and also see how consistent each driver's efficiency is. Which of the following approaches is the best course of action?

Accepted Answer

Create a box plot grouped by DriverID showing the distribution of MPG for each driver.. A box plot grouped by DriverID is the best choice because it simultaneously shows the central tendency (median MPG) and the spread (interquartile range and outliers) of each driver's fuel efficiency. This allows management to quickly compare average efficiency across drivers while also assessing consistency—drivers with narrow boxes are more consistent, while those with wide boxes or many outliers are erratic. The other options either fail to show distribution (bar chart, line chart) or require manual interpretation of consistency (scatter plot).

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Create a line chart with Date on the x-axis and MPG on the y-axis, with separate lines for each driver.

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Create a scatter plot with Distance on the x-axis and FuelUsed on the y-axis, color-coded by DriverID.

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Create a bar chart showing the average MPG for each driver.