DA0-002 Exam Dumps - CompTIA Data+ Questions and Answers

This question falls under the Data Analysis domain, focusing on SQL queries to handle duplicates while counting employees. The task is to count unique employees with a salary of $125,000 or more, addressing duplicates in the dataset.

Option A: SELECT DISTINCT Employee_ID FROM Employee WHERE Salary >= 125000This lists unique Employee_IDs but doesn’t provide a count, which the department needs.

Option B: SELECT COUNT(DISTINCT Employee_ID) FROM Employee WHERE Salary >= 125000This counts unique Employee_IDs (using DISTINCT) with a salary of $125,000 or more, correctly addressing duplicates and providing the required count (2 employees: 003 and 004).

Option C: SELECT DISTINCT Employee_ID FROM Employee WHERE Salary > 125000This lists unique Employee_IDs with a salary strictly greater than $125,000 (missing 004), and doesn’t provide a count.

Option D: SELECT COUNT(Employee_ID) FROM Employee WHERE Salary >= 125000This counts all rows without addressing duplicates, resulting in an incorrect count (2 rows, but only 2 unique employees).

The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and COUNT(DISTINCT) is the correct method to count unique employees while handling duplicates.

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 Data Concepts and Environments domain, focusing on data repositories. The task is to identify a repository that stores raw, unformatted data.

Data warehouse (Option A): A data warehouse stores structured, processed data in a predefined schema, not raw data.

Data silo (Option B): A data silo is an isolated repository, often structured, not designed for raw data storage.

Data mart (Option C): A data mart is a subset of a data warehouse, also storing structured data.

Data lake (Option D): A data lake stores raw, unformatted data in its original format (structured, semi-structured, or unstructured), making it the correct choice.

The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases and data repositories," and a data lake is designed for raw data storage.

This question pertains to the Data Concepts and Environments domain, focusing on types of server infrastructure. The task is to identify an infrastructure where a company owns and maintains all servers.

Private (Option A): A private infrastructure (often on-premises) means the company owns and maintains its own servers, typically in a private data center, which matches the requirement.

Cloud (Option B): Cloud infrastructure is managed by third-party providers, not owned by the company.

Hybrid (Option C): Hybrid combines on-premises and cloud, so not all servers are owned by the company.

Public (Option D): Public infrastructure is a cloud model shared across multiple organizations, not owned by the company.

The DA0-002 Data Concepts and Environments domain includes understanding "data environments," and a private infrastructure requires the company to purchase and maintain its own servers.

This question pertains to the Data Governance domain, focusing on data classification for security purposes. User information databases typically contain personal data, and security triggers (e.g., alerts for unauthorized access) require classifying data to determine protection levels.

Public (Option A): Public data is openly accessible (e.g., company brochures), not suitable for user information requiring security triggers.

Open (Option B): Open isn’t a standard data classification; it’s similar to public and not applicable here.

Sensitive (Option C): Sensitive data includes information that, if exposed, could cause harm (e.g., user emails, roles), which fits user information and warrants security triggers.

Non-Sensitive (Option D): Non-sensitive data doesn’t require protection, so it wouldn’t need security triggers.

Private (Option E): Private data includes PII (e.g., names, addresses) in user information databases, requiring security measures like triggers to protect against breaches.

Encrypted (Option F): Encrypted refers to a data state, not a classification; data can be classified as private or sensitive and then encrypted.

The DA0-002 Data Governance domain includes "data quality control concepts," such as classifying data to apply appropriate security measures. Sensitive and private classifications are most relevant for user information.

This question falls under the Visualization and Reporting domain of DA0-002, which involves selecting appropriate delivery methods for reports. The scenario describes a need for custom reports for future executive meetings, implying a scheduled, repeated delivery.

Ad hoc (Option A): Ad hoc reports are generated on-demand for one-time use, not suitable for ongoing needs.

Real-time (Option B): Real-time delivery provides live data updates, which isn’t necessary for scheduled executive meetings.

Recurring (Option C): Recurring delivery involves scheduling reports to be generated and delivered at regular intervals (e.g., weekly or monthly), which fits the need for future executive meetings.

Self-service (Option D): Self-service allows users to generate reports themselves, but the scenario implies the analyst will create the reports.

The DA0-002 Visualization and Reporting domain includes understanding "the appropriate visualization in the form of a report" with delivery methods , and recurring delivery aligns with scheduled reporting needs.

This question pertains to the Visualization and Reporting domain, focusing on selecting the appropriate visualization to show a relationship between two continuous variables (ages and incomes).

Scatter plot (Option A): A scatter plot displays individual data points on two axes (age vs. income), making it ideal for showing the relationship and potential correlation between two continuous variables.

Area plot (Option B): Area plots are used for showing trends over time, not relationships between two variables.

Bar chart (Option C): Bar charts are better for categorical data comparisons, not continuous variable relationships.

Pie chart (Option D): Pie charts show proportions of a whole, not suitable for showing relationships between variables.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a scatter plot is best for showing the relationship between age and income.

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 pertains to the Data Acquisition and Preparation domain, focusing on tools for automating repeatable tasks in data processes. The task is to identify the most efficient programming method.

LLM (Option A): Large Language Models (e.g., GPT) are for text generation, not efficient for repeatable data tasks.

Deep learning (Option B): Deep learning is for complex pattern recognition (e.g., image classification), not efficient for simple repeatable tasks.

NLP (Option C): Natural Language Processing is for text analysis, not general repeatable tasks.

RPA (Option D): Robotic Process Automation (RPA) automates repetitive, rule-based tasks (e.g., data entry, file processing), making it the most efficient for programming repeatable tasks.

The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and RPA is a widely used method for automating repeatable data tasks.

This question falls under the Visualization and Reporting domain, focusing on selecting the appropriate visualization to identify outliers in a dataset.

Box plot (Option A): A box plot displays the distribution of data, including the median, quartiles, and outliers (data points beyond the whiskers), making it the best choice for identifying outliers.

Scatter plot (Option B): A scatter plot shows relationships between two variables, and while outliers may be visible, it’s not specifically designed for outlier detection.

Gantt chart (Option C): Gantt charts are for project scheduling, not suitable for outlier identification.

Waterfall chart (Option D): Waterfall charts show cumulative changes (e.g., financial contributions), not designed for outlier detection.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a box plot is the standard visualization for identifying outliers.