Free Practice Questions for CompTIA Data+ Certification
Study with 345 exam-style practice questions designed to help you prepare for the CompTIA Data+.
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Exam Details
Key information about CompTIA Data+
- Multiple choice
- Matching
90 minutes
English
Usually three years after launch (estimated 2028)
October 14, 2025
V2
675 (on a scale of 100–900)
DA0-002
Maximum of 90 (multiple-choice and performance-based)
18–24 months in a data analyst or similar job role, with exposure to databases, analytical tools, basic statistics, and data visualization
ISO accredited by the ANSI National Accreditation Board (ANAB), and mapped to the NICE Framework Data Analyst (IO-WRL-001) work role.
Exam Topics & Skills Assessed
Skills measured (from the official study guide)
Domain 1: Data concepts and environments
Subdomain 1.1: Explain data concepts
Explain data concepts: Database types, data structures, file extensions, and data types.
Subdomain 1.2: Identify data sources
Identify data sources: Databases, APIs, website data, files, logs and repositories.
Subdomain 1.3: Recognize infrastructure concepts
Recognize infrastructure concepts: Cloud, on-premise, storage, and containerization.
Subdomain 1.4: Identify data tools
Identify data tools: Coding environments, BI software, and analysis platforms.
Subdomain 1.5: Understand AI concepts
Understand AI concepts: Identify AI models, natural language processing, and robotic automation.
Domain 2: Data acquisition and preparation
Subdomain 2.1: Use data acquisition methods
Use data acquisition methods: Data integration and queries to gather and combine data.
Subdomain 2.2: Perform data exploration
Perform data exploration: Find missing values, duplication, redundancy, or outliers.
Subdomain 2.3: Apply data transformation
Apply data transformation: Cleansing, merging, parsing, and formatting data.
Domain 3: Data analysis
Subdomain 3.1: Communicate analysis results
Communicate analysis results: Select methods for different audiences.
Subdomain 3.2: Select statistical methods
Select statistical methods: Apply basic statistical techniques to data.
Subdomain 3.3: Troubleshoot analysis issues
Troubleshoot analysis issues: Use tools and resources to resolve problems.
Domain 4: Visualization and reporting
Subdomain 4.1: Create effective visuals
Create effective visuals: Use charts, maps, tables, and design elements.
Subdomain 4.2: Deliver reports
Deliver reports: Provide dashboards or summaries using appropriate methods.
Subdomain 4.3: Validate reporting accuracy
Validate reporting accuracy: Apply validation and review to solve reporting issues
Domain 5: Data governance
Subdomain 5.1: Explain data management practices
Explain data management practices: Documentation, versioning, and data lineage.
Subdomain 5.2: Summarize compliance requirements
Summarize compliance requirements: Retention, audits, and regulations.
Subdomain 5.3: Compare privacy and protection strategies
Compare privacy and protection strategies: Access control, encryption, and masking.
Subdomain 5.4: Implement quality assurance
Implement quality assurance: Profiling, monitoring, and testing for data quality.
Techniques & products