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CompTIA DA0-002 Exam Questions
- Topic 1: Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
- Topic 2: Data Mining: This section of the exam measures skills of a Business Intelligence Analyst and covers how data is collected, cleaned, and prepared for analysis. It explains methods like ETL and ELT for data integration, as well as web scraping, API use, and survey data collection. Candidates are expected to identify issues like missing or duplicated data and apply techniques like filtering, sorting, merging, and normalizing. The section also touches on query optimization strategies to improve data handling efficiency.
- Topic 3: Data Analysis: This section of the exam measures skills of a Reporting Analyst and includes foundational knowledge of statistical methods such as averages, variances, and standard deviation. It covers how to use data to find patterns, track performance, and make predictions. This domain also introduces hypothesis testing, regression, correlation, and different types of analysis like exploratory and trend analysis. Candidates should also be aware of common tools used for analysis, including Excel, SQL, Python, R, and popular BI platforms like Tableau and Power BI.
- Topic 4: Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.
- Topic 5: 5.0 Data Governance, Quality, and Controls This section of the exam measures skills of a Data Governance Associate and introduces principles for keeping data secure, accurate, and compliant. It covers access controls, encryption, classification of sensitive data like PII and PHI, and legal requirements tied to data use. Candidates must know how to apply quality checks, validate data, and manage master data effectively. It also addresses best practices for maintaining integrity through data dictionaries, audits, and standardisation processes.
Free CompTIA DA0-002 Exam Actual Questions
Note: Premium Questions for DA0-002 were last updated On Apr. 06, 2026 (see below)
A company's entire server environment is located at the company's headquarters. Which of the following describes this type of environment?
This question pertains to the Data Concepts and Environments domain, focusing on types of server environments. The servers are located at the company's headquarters, indicating a specific deployment model.
Cloud (Option A): Cloud environments are hosted off-site by third-party providers, not at headquarters.
On-premises (Option B): On-premises environments are located at the company's physical location (e.g., headquarters), which matches the scenario.
Public (Option C): Public environments are cloud-based and shared across multiple organizations, not located at headquarters.
Hybrid (Option D): Hybrid environments combine on-premises and cloud, but the scenario specifies all servers are at headquarters.
The DA0-002 Data Concepts and Environments domain includes understanding 'data environments,' and on-premises describes a server environment located at the company's site.
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Which of the following best describes an assessment a data analyst would use to validate that the number of records in a dataset matches the expected results?
This question pertains to the Data Governance domain, focusing on data quality validation techniques. The task is to validate that the number of records matches expectations, which requires a specific type of assessment.
Source control (Option A): Source control (e.g., Git) manages code versions, not dataset validation.
Unit test (Option B): A unit test checks a specific component of a process, such as verifying that the number of records in a dataset matches the expected count, making it the best fit.
Stress test (Option C): Stress tests evaluate system performance under load, not record counts.
Health check (Option D): A health check monitors system status but isn't specific to validating record counts.
The DA0-002 Data Governance domain includes 'data quality control concepts,' and unit tests are a standard method for validating specific data outcomes like record counts.
Which of the following data repositories stores unstructured and structured data?
This question falls under the Data Concepts and Environments domain of CompTIA Data+ DA0-002, which involves understanding different types of data repositories and their characteristics. The task is to identify a repository that can store both unstructured and structured data.
Data store (Option A): A data store is a general term for any data repository, but it's not specific enough to confirm it stores both unstructured and structured data.
Data silo (Option B): A data silo is an isolated data repository, often structured, and not typically designed for unstructured data.
Data mart (Option C): A data mart is a subset of a data warehouse, focused on structured data for specific business areas, not unstructured data.
Data lake (Option D): A data lake is a centralized repository that stores raw data in its native format, including both structured (e.g., tables) and unstructured (e.g., text, images) data, 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 specifically designed to handle both unstructured and structured data.
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The sales department wants to include the composition of total sales amounts across all three sales channels in a report. Given the following sample sales table:
Sales channel
Month
Sales (million $)
Digital
January
135
Store
February
145
Online
March
165
Store
April
200
Store
May
125
Online
June
155
Digital
July
120
Online
August
145
Digital
September
160
Which of the following visualizations is the most appropriate?
This question pertains to the Visualization and Reporting domain, focusing on selecting the appropriate visualization for a specific requirement. The task is to show the composition of total sales across three channels, which involves showing proportions.
Pivot table (Option A): A pivot table summarizes data but isn't a visualization; it's more for data exploration.
Pie chart (Option B): A pie chart shows the proportion of total sales for each channel (Digital, Store, Online), which is ideal for displaying composition.
KPI card (Option C): A KPI card displays a single metric, not suitable for showing composition across multiple channels.
Box plot (Option D): A box plot shows data distribution (e.g., quartiles), not proportions.
The DA0-002 Visualization and Reporting domain emphasizes 'translating business requirements to form the appropriate visualization,' and a pie chart is best for showing the composition of totals.
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[Data Governance]
A data analyst receives a new data source that contains employee IDs, job titles, dates of birth, addresses, years of service, and employees' birth months. Which of the following inconsistencies should the analyst identify?
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