CompTIA DA0-001 Exam Details & Actual Exam Questions
- Exam Code/Number: DA0-001
- Exam Name/Title: CompTIA Data+ Certification Exam
- Certification Provider: CompTIA
- Corresponding Certification: CompTIA Data+
- Exam Questions: 398
- Updated On: Jul,18 2026
- Certification Level: Associate
CompTIA Data+ Certification Exam Questions
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(27 Up Votes)CompTIA DA0-001 Exam Overview:
| Certification Vendor: | CompTIA |
| Exam Name: | CompTIA Data+ Certification Exam |
| Exam Number: | DA0-001 |
| Exam Price: | $253 USD / £150 GBP / €228 EUR |
| Available Languages: | English, Japanese, Thai |
| Passing Score: | 675 (on a scale of 100–900) |
| Related Certifications: | CompTIA A+ CompTIA Network+ CompTIA Security+ |
| Real Exam Qty: | Up to 90 |
| Certificate Validity Period: | 3 years |
| Exam Format: | Multiple-choice, Performance-based |
| Exam Duration: | 90 minutes |
| Recommended Training: | CompTIA CertMaster Learn CompTIA Official Study Materials |
| Exam Registration: | Pearson VUE Scheduling CompTIA Official Registration |
| Sample Questions: | CompTIA DA0-001 Sample Questions |
| Exam Way: | Online remote proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Recommended: 18–24 months of experience in report/business analysis, exposure to databases and analytical tools, basic statistics knowledge, and data visualization experience; no mandatory prerequisites |
| Official Syllabus URL: | https://www.comptia.org/certifications/data |
CompTIA DA0-001 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Mining | 25% | - Data acquisition and integration methods - Querying and retrieving data - Data transformation, manipulation, and enrichment - Data profiling, cleansing, and validation |
| Data Governance, Quality and Controls | 14% | - Data lifecycle management and controls - Data quality standards and measurement - Data privacy, security, and compliance - Data governance frameworks and policies |
| Visualization and Reporting | 23% | - Selecting appropriate visualizations and charts - Design principles and best practices - Building dashboards and reports - Communicating insights and recommendations |
| Data Concepts and Environments | 15% | - Data storage systems: databases, data marts, warehouses, data lakes - Data schemas, dimensions, and attributes - Structured, semi-structured, and unstructured data - Data types, structures, and formats |
| Data Analysis | 23% | - Interpreting results and identifying patterns/anomalies - Statistical methods: correlation, regression, hypothesis testing - Analytical techniques: trend, performance, exploratory, comparative - Descriptive and inferential statistics |
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