DA0-002 Exam Simulation 1 — 100 Questions

Question 1

A data analyst needs to count the number of customers who have placed at least one order. Which SQL query should be used?

Accepted Answer

SELECT COUNT(DISTINCT customer_id) FROM orders. COUNT(DISTINCT customer_id) counts each unique customer exactly once, which is precisely what is needed to answer 'how many customers placed at least one order' — a customer with multiple orders is counted only once. This is the standard SQL pattern for counting distinct entities in a fact table.

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SELECT DISTINCT COUNT(customer_id) FROM orders

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SELECT SUM(customer_id) FROM orders

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SELECT COUNT(customer_id) FROM orders

Question 2

A marketing team uses K-means clustering to segment customers based on purchase history. To determine the optimal number of clusters, they plot the within-cluster sum of squares (WCSS) against k and look for an elbow. What is the purpose of this method?

Accepted Answer

To find the point where the rate of decrease in WCSS slows down. The elbow method helps choose k where adding more clusters yields diminishing returns in reducing variance.

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To identify the value of k that minimizes WCSS

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To determine the initial centroids for the algorithm

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To ensure all clusters have equal size

Question 3

During an ETL process, a data quality check fails due to duplicate customer IDs. Which data quality dimension is violated?

Accepted Answer

Uniqueness. Duplicate customer IDs violate the uniqueness dimension because uniqueness ensures that each record in a dataset has a distinct identifier with no duplicates. In an ETL process, a primary key or unique constraint on the customer ID column would reject duplicate values, causing the data quality check to fail. This is distinct from consistency, which checks for logical agreement across data sources.

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Consistency

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Completeness

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Accuracy

Question 4

A dashboard designer is creating a sales performance dashboard and wants to minimize non-data ink to improve clarity. Which action best follows the principle of maximizing the data-ink ratio?

Accepted Answer

Removing gridlines that do not add value to the chart. It directly follows Tufte's data-ink ratio principle by removing non-data ink (gridlines that don't aid interpretation) while preserving the core data. This maximizes the proportion of ink devoted to actual sales metrics, improving clarity without sacrificing information.

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Including a detailed company logo on every chart

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Adding a background image to make the dashboard more visually appealing

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Using 3-D effects on bars to make them stand out

Question 5

A data analyst creates a report showing sales by product category. The analyst notices that one category has a very high sales figure due to a one-time bulk order. Which of the following is the best way to communicate this insight to stakeholders?

Accepted Answer

Add a note to the chart explaining the bulk order.. It maintains data integrity while providing necessary context. Adding a note to the chart allows stakeholders to understand the anomaly without distorting the underlying data. This approach aligns with best practices in data communication, where transparency about outliers is critical for accurate interpretation.

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Delete the bulk order from the dataset.

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Remove the category with the bulk order from the report.

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Use a pie chart to show the proportion of each category.

Question 6

An analyst creates a dashboard with a large amount of decorative graphics and background images. According to CompTIA Data+, which design principle is being violated?

Accepted Answer

Data-ink ratio. The data-ink ratio, a concept from Edward Tufte, states that a visualization should maximize the proportion of ink used to represent actual data relative to total ink used. By adding excessive decorative graphics and background images, the analyst reduces this ratio, making the dashboard less efficient and potentially obscuring the data. CompTIA Data+ emphasizes minimizing non-data ink to improve clarity and insight extraction.

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Visual hierarchy

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Appropriate precision

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Consistent color coding

Question 7

A small business wants to acquire customer feedback through a short questionnaire emailed after purchase. Which data acquisition method does this represent?

Accepted Answer

Survey. A survey is a structured data collection method where respondents answer predefined questions, typically via a form or questionnaire. In this scenario, the business is using a short questionnaire emailed after purchase to gather customer feedback, which directly aligns with the definition of a survey as a data acquisition method.

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Transaction log

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Interview

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Observation

Question 8

A large online retailer stores customer orders in a PostgreSQL database. Each order has a unique order ID, and the database is normalized to 3NF. Which type of data is this?

Accepted Answer

Structured data. The data is structured because it resides in a normalized PostgreSQL database with a unique order ID and conforms to a fixed schema (3NF). Structured data is organized into rows and columns with defined data types, enabling efficient SQL querying and ACID compliance. PostgreSQL's relational model enforces this structure through tables, constraints, and indexes.

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Semi-structured data

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Unstructured data

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Metadata

Question 9

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.

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Revamp the dashboard with as many visualizations as possible.

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Conduct a survey of all employees to understand their needs.

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Create a static PDF report instead of a dashboard.

Question 10

A business analyst wants to show the relationship between advertising spend (independent variable) and sales revenue (dependent variable) for 12 different regions. Each region will be represented by a point. Which chart type is most appropriate?

Accepted Answer

Scatter plot. A scatter plot is the most appropriate chart type because it directly visualizes the relationship between two continuous variables—advertising spend (independent) and sales revenue (dependent)—by plotting each of the 12 regions as a point. This allows the analyst to assess correlation, trends, and outliers, which is the core purpose of scatter plots in data visualization.

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Line chart

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Bar chart

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Histogram

Question 11

A dashboard designer wants to ensure the most important KPI is prominently displayed at the top left. Which design principle is being applied?

Accepted Answer

Visual hierarchy. Visual hierarchy arranges elements by importance, typically placing the most critical information where the eye naturally starts (top left in Western cultures).

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Consistent color coding

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Data-ink ratio

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Appropriate precision

Question 12

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.

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Trigger

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Stored procedure

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Index

Question 13

In SQL, you want to retrieve all products whose names start with 'Pro'. Which WHERE clause should you use?

Accepted Answer

WHERE product_name LIKE 'Pro%'. LIKE with pattern 'Pro%' matches strings starting with 'Pro' followed by any characters. '%Pro%' matches any string containing 'Pro', 'Pro_' matches 'Pro' plus one character, and 'Pro' is exact match.

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WHERE product_name LIKE '%Pro%'

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WHERE product_name LIKE 'Pro_'

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WHERE product_name = 'Pro'

Question 14

Drag and drop the steps to perform a data audit in the correct order.

Accepted Answer

1. Inventory, 2. Quality Assessment, 3. Compliance Check, 4. Documentation, 5. Recommendations. Data audit begins with inventory, quality assessment, compliance check, documentation, and recommendations.

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1. Quality Assessment, 2. Inventory, 3. Compliance Check, 4. Documentation, 5. Recommendations

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1. Inventory, 2. Compliance Check, 3. Quality Assessment, 4. Documentation, 5. Recommendations

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1. Inventory, 2. Quality Assessment, 3. Documentation, 4. Compliance Check, 5. Recommendations

Question 15

A healthcare data analyst is presenting findings on patient readmission rates to a group of hospital administrators. The analysis reveals a 15% increase in readmissions over the past quarter for patients aged 65+ from a specific zip code. However, the administrators are skeptical because previous quarterly reports showed no such trend, and they suspect data quality issues. The analyst must communicate this insight effectively while maintaining credibility. Which of the following approaches should the analyst take?

Accepted Answer

Acknowledge the discrepancy and explain possible reasons such as changes in data collection methods or patient population. It demonstrates the core competency of 'Communicating Data Insights' by acknowledging the discrepancy between the current finding and previous reports, which builds trust with skeptical stakeholders. By explaining possible reasons such as changes in data collection methods or patient population, the analyst maintains credibility and invites collaborative investigation into data quality issues, rather than dismissing concerns or hiding details.

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Emphasize the statistical significance of the finding and ignore previous reports

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Present the data without any explanation and let them draw conclusions

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Remove the demographic detail to avoid controversy

Question 16

A data analyst is creating a dashboard in Looker Studio and needs to combine data from two different data sources using a common field. Which feature should be used?

Accepted Answer

Data blending. Data blending in Looker Studio allows you to combine data from multiple data sources into a single chart or table by joining them on a common dimension (key field). This is the correct feature when you need to merge data from two different sources, such as Google Analytics and Google Sheets, using a shared field like date or campaign ID.

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Community connector

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Filter

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Calculated field

Question 17

An IT operations team monitors 200 servers. Each server reports CPU utilization (0-100%) every five minutes for the past year. The team wants to visualize the data to identify servers that are consistently over 80% utilization and detect any unusual spikes. They have a large dataset with 100,000+ records per server. The current visualization is a single scatter plot with CPU utilization on the y-axis, time on the x-axis, and each server as a different colored point. The chart is extremely cluttered, with points overlapping and colors indistinguishable. What should the team do to improve the visualization?

Accepted Answer

Use a heatmap showing CPU utilization over time per server, or create small multiple charts (one per server). With 200 servers and 100,000+ records per server, a single scatter plot is too cluttered. A heatmap can show CPU utilization over time per server using color intensity, or small multiples (one chart per server) can separate the data. Both approaches reduce overlap and make patterns like consistent over-80% utilization and spikes visible.

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Switch to a line chart with each server as a separate line

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Add a trend line to each server's data and remove the individual points

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Increase the size of the data points to make them more visible

Question 18

A healthcare analytics team is analyzing patient readmission rates. They have a dataset with thousands of records including patient age, diagnosis, length of stay, number of prior admissions, and discharge date. The goal is to identify key factors influencing readmission and create a model to predict high-risk patients. The data is imbalanced: only 5% of patients are readmitted within 30 days. The team plans to use logistic regression. What is the most appropriate approach?

Accepted Answer

Apply oversampling techniques like SMOTE to the training set. With imbalanced data, logistic regression can be biased toward the majority class. Oversampling the minority class (e.g., SMOTE) helps the model learn patterns for readmission. Using accuracy as a metric would be misleading. Removing majority samples discards valuable data. Using data as-is often fails to predict the minority class.

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Use the dataset as is because logistic regression handles imbalance

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Remove most of the non-readmitted patients to balance the dataset

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Use accuracy as the evaluation metric

Question 19

A data analyst wants to show the relationship between advertising spend and sales revenue for 50 stores. Which chart type is most appropriate?

Accepted Answer

Scatter plot. A scatter plot is the most appropriate chart for showing the relationship between two continuous variables—advertising spend and sales revenue—across 50 stores. Each point on the plot represents one store, allowing the analyst to visually assess correlation, trends, or outliers. This aligns with the DA0-001 objective of selecting visualizations that best represent bivariate relationships.

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Line chart

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Bar chart

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Pie chart

Question 20

A company is designing a database for an e-commerce application that requires high transaction throughput and must guarantee that each transaction is processed atomically. Which property of ACID ensures that a transaction is either fully completed or not executed at all?

Accepted Answer

Atomicity. Atomicity is the ACID property that guarantees a transaction is treated as a single indivisible unit — either all of its operations commit or none of them do. If any statement in the transaction fails, the entire transaction is rolled back, leaving the database in its pre-transaction state. This is the 'all-or-nothing' guarantee that the question describes.

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Isolation

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Durability

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Consistency