Free Practice Questions for CompTIA Data+ Certification
- Guide checked for updates:
- 9 Oct 2026
- Question bank created:
- 19 Sep 2026
- Question bank last updated:
- 20 Sep 2026
Study with 340 exam-style practice questions designed to help you prepare for the CompTIA Data+. All questions are aligned with the latest exam guide and include detailed explanations to help you master the material.
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Quiz History
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)
1: Data Concepts and Environments
1.1: Explain data concepts.
1.2: Identify types of data sources.
1.3: Identify infrastructure concepts.
1.4: Identify common data analysis tools.
1.5: Identify artificial intelligence (AI) concepts.
2: Data Acquisition and Preparation
2.1: Given a scenario, use data acquisition methods.
2.2: Given a scenario, perform data exploration to identify possible inconsistencies with a data set.
2.3: Given a scenario, perform appropriate data transformation and cleansing techniques.
3: Data Analysis
3.1: Given a set of requirements, determine the appropriate communication approach for data analysis.
3.2: Given a scenario, select the appropriate statistical method or function.
3.3: Given a scenario, troubleshoot basic issues using the appropriate tool or method.
4: Visualization and Reporting
4.1: Given a scenario, use the appropriate visual elements.
4.2: Given a scenario, use the appropriate delivery or consumption method.
4.3: Given a scenario, troubleshoot issues using report validation techniques.
5: Data Governance
5.1: Explain data management concepts.
5.2: Summarize concepts related to data compliance.
5.3: Compare and contrast data privacy and protection practices.
5.4: Compare and contrast data quality assurance practices.
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