DA0-002 Exam Dumps - CompTIA Data+ Exam (2025)

This question falls under the Visualization and Reporting domain of CompTIA Data+ DA0-002, focusing on selecting the appropriate visualization for a specific dataset. The task is to show availability zones over a 15-year period (past and future), which involves a geographical element since availability zones are typically location-based.

Bar chart (Option A): Bar charts are good for comparing categorical data but don’t effectively show geographical locations or time-based trends across zones.

Mosaic plot (Option B): Mosaic plots display relationships between categorical variables, not suitable for geographical or time-series data.

Map (Option C): A map can display availability zones geographically, with annotations or layers to show changes over time (past 10 years and future 5 years), making it the most appropriate visualization.

Pie chart (Option D): Pie charts show proportions of a whole, not suitable for geographical or time-based data.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a map is the best choice for displaying geographical availability zones over time.

This question falls under the Data Governance domain of CompTIA Data+ DA0-002, focusing on troubleshooting data quality issues in dashboards. The dashboard isn’t loading properly, indicating a potential issue with the data connection or configuration.

Review the data layer and data source (Option A): The data layer (e.g., queries, connections) and data source (e.g., database) are the foundation of a dashboard. If the information isn’t loading, the issue likely lies in the data connection or query configuration, making this the first step.

Validate that the database is up-to-date (Option B): While this might be a subsequent step, it assumes the connection is working, which should be confirmed first.

Check that the program is updated to the latest version (Option C): Software updates might fix bugs, but this isn’t the most immediate cause of data not loading.

Ensure the correct filters are displaying on the dashboard (Option D): Filters affect data display, but if the data isn’t loading at all, the issue is more fundamental.

The DA0-002 Data Governance domain includes "data quality control concepts," and reviewing the data layer and source is the primary step in troubleshooting dashboard loading issues.

This question falls under the Data Analysis domain, focusing on analytical methods for reporting. The task is to identify the causes of customer churn over three years, which involves analyzing historical data.

Inferential (Option A): Inferential statistics make predictions or generalizations about a population, not focused on identifying causes in historical data.

Descriptive (Option B): Descriptive analytics summarizes historical data to identify patterns and causes (e.g., reasons for churn), which fits the task.

Prescriptive (Option C): Prescriptive analytics provides recommendations, which goes beyond identifying causes.

Predictive (Option D): Predictive analytics forecasts future outcomes, not focused on historical causes.

The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and descriptive analytics is best for identifying causes in historical data.

This question falls under the Data Acquisition and Preparation domain, focusing on combining tables to produce a dataset. The task requires combining the Courses and Students tables to include student names with course details, based on the StudentID.

Aggregate (Option A): Aggregation (e.g., SUM, COUNT) summarizes data, not suitable for combining tables to include names.

Join (Option B): A join operation (e.g., INNER JOIN on StudentID) combines the tables, matching records to produce the requested output with CourseID, SectionNumber, StudentID, FirstName, and LastName.

Group (Option C): Grouping is used for aggregation (e.g., GROUP BY in SQL), not for combining tables.

Filter (Option D): Filtering selects specific rows, not relevant for combining tables.

The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as joining tables to create a unified dataset.

This question pertains to the Visualization and Reporting domain, focusing on the initial steps in dashboard creation. The analyst is starting a project for multiple teams, so understanding the audience is critical.

Evaluate the user persona type for the dashboards (Option A): User personas define the needs, roles, and preferences of the audience (e.g., executives vs. analysts), which is the first step to ensure the dashboards meet user requirements.

Determine the number of team members who need to access the dashboards (Option B): This is important for access control but not the first step in design.

Determine the delivery method of the dashboards (Option C): Delivery method (e.g., self-service) is decided later, after understanding user needs.

Evaluate the KPIs for the dashboards (Option D): KPIs are defined after understanding the user personas and their goals.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and evaluating user personas is the first step in this process.

This question pertains to the Visualization and Reporting domain, focusing on dashboard design for specific audiences. Internal technical audiences (e.g., data analysts, IT staff) need actionable, data-driven insights.

Methodology section (Option A): Methodology is important for research reports, not dashboards, especially for technical audiences who prioritize data.

Dynamic features (Option B): Dynamic features (e.g., interactivity) are useful but not the most critical element for technical audiences.

Key performance indicators (Option C): KPIs provide critical metrics (e.g., system uptime, error rates) that technical audiences need to monitor and act on, making this the most important element.

Company branding (Option D): Branding is more relevant for external audiences, not internal technical ones.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and KPIs are essential for technical dashboards.

This question pertains to the Data Concepts and Environments domain, focusing on data sources that facilitate online data access. The task is to identify a source that simplifies online data consumption.

Data mart (Option A): A data mart stores structured data for specific business areas, typically accessed internally, not designed for online consumption.

Web scraping (Option B): Web scraping extracts data from websites but requires parsing and cleaning, which isn’t necessarily "easier."

Database (Option C): Databases store data but aren’t inherently designed for online consumption without an interface.

Application programming interface (Option D): An API provides a structured way to access data online, often in formats like JSON, making data consumption easier for applications and users.

The DA0-002 Data Concepts and Environments domain includes understanding "data sources," and APIs are specifically designed to simplify online data access.

This question falls under the Data Governance domain, focusing on data access and security troubleshooting. The analyst reset their password, but the recurring analysis failed to log in, indicating a mismatch.

The company changed its database authentication method (Option A): This would affect all users, not just the analyst, and there’s no indication of a broader change.

The password expiration process locked the account (Option B): The analyst reset the password as required, so the account isn’t likely locked due to expiration.

The analyst did not change the password used to launch the report (Option C): Recurring analyses often use stored credentials. If the analyst updated their password but didn’t update the stored credentials for the analysis, the login would fail, making this the most likely reason.

The company is experiencing issues with password replication (Option D): This is possible but less likely without evidence of broader system issues.

The DA0-002 Data Governance domain includes "data privacy concepts," and ensuring stored credentials match updated passwords is a common issue in recurring analyses.