CompTIA DA0-001 Practice Test Questions Answers
Exam Code: DA0-001
(Updated 363 Q&As with Explanation)
Exam Name: CompTIA Data+ Certification Exam
Last Update: 05-Apr-2025
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DA0-001 Overview
CompTIA DA0-00 Exam Overview
| Category | Details |
|---|---|
| Certification Name | CompTIA Data+ (DA0-001) |
| Target Audience | Individuals looking to start a career in data analysis, including those in data management, data quality, data governance, and analytics roles. |
| Purpose | To validate foundational knowledge and skills related to data analysis and data management, including data governance, data visualization, and basic analytics. |
| Exam Duration | 90 minutes |
| Number of Questions | 60 questions |
| Passing Score | 700 (out of 900) |
| Exam Format | Multiple-choice and performance-based questions |
| Exam Delivery | Online (via Pearson VUE or authorized CompTIA testing centers) |
| Exam Cost | $226 (USD) |
| Languages Available | English, Japanese |
| Prerequisites | No formal prerequisites, but a basic understanding of IT and some data analysis experience is recommended. |
| Key Topics Covered | 1. Data Management 2. Data Analysis 3. Data Visualization 4. Data Governance 5. Data Quality 6. Basic Statistical Analysis |
| Preparation Resources | 1. CompTIA Data+ Study Guide 2. CompTIA Learning Path 3. Practice exams and courses 4. Online forums and webinars |
| Validity Period | 3 years (requires recertification after expiration) |
| Retake Policy | Candidates who do not pass may retake the exam after waiting 14 days. |
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CompTIA DA0-001 Exam Topics Breakdown
| Domain | Weight (%) | Topics Covered |
|---|---|---|
| 1. Data Management | 20% | - Understanding data sources and types - Data storage and management concepts - Data integration techniques |
| 2. Data Analysis | 25% | - Understanding statistical analysis - Data modeling and interpretation - Use of data analysis tools (Excel, SQL, etc.) |
| 3. Data Visualization | 15% | - Data visualization concepts - Using tools like Power BI, Tableau, or Excel for visualizing data insights - Creating reports and dashboards |
| 4. Data Governance | 15% | - Data privacy and security - Compliance with regulations (GDPR, CCPA, etc.) - Implementing data governance policies |
| 5. Data Quality | 15% | - Ensuring data accuracy, consistency, and reliability - Data cleaning techniques - Identifying and resolving data quality issues |
| 6. Basic Statistical Analysis | 10% | - Descriptive statistics (mean, median, mode, etc.) - Data distributions - Basic inferential statistics |
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