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Updated: Sep 22, 2026
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CompTIA DA0-001 Exam Overview:
| Certification Vendor: | CompTIA |
|---|---|
| Exam Name: | CompTIA Data+ Certification Exam |
| Exam Number: | DA0-001 |
| Real Exam Qty: | Up to 90 |
| Available Languages: | English, Thai, Japanese |
| Exam Format: | Performance-based, Multiple-choice |
| Exam Duration: | 90 minutes |
| Certificate Validity Period: | 3 years |
| Passing Score: | 675 (on a scale of 100–900) |
| Exam Price: | $253 USD / £150 GBP / €228 EUR |
| Related Certifications: | CompTIA Security+ CompTIA A+ CompTIA Network+ |
| 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 |
Understanding CompTIA DA0-001 Exam Topics
Applying basic statistical methods
Manipulating data
Mining data
Visualizing and reporting data
Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
Reference: https://www.comptia.org/training/books/data-da0-001-study-guide
Passing Score, Duration & Questions For The CompTIA DA0-001 Exam
- Exam Length: 90 questions
- The passing score: 675 (on scale of 100-900)
- Languages: English
- Time Duration: 90 minutes
- Format: Multiple choice and performance-based
What are the special features of the CompTIA DA0-001 Exam
The CompTIA Data+ certification is an important one, because it's the first of its kind. It was developed to ensure that IT professionals had the necessary skills to work with data and perform advanced analysis.
The CompTIA Data+ certification is also unique in that it can be applied across several different industries. In fact, the curriculum for this exam focuses on three different areas: data analysis, communication and technology. This means that you'll need a strong understanding of all three areas to qualify for this exam. CompTIA DA0-001 exam dumps are the best way to make you perp fast.
The CompTIA Data+ certification is designed for those who have already gained experience working with data or those who want to learn more about it. The test consists of a series of questions designed to measure your knowledge about various aspects of data analysis.
Objectives of CompTIA DA0-001 Exam
In this section, we will list the objectives you should know in order to pass your CompTIA Data+ certification exam.
The first objective is to understand how to become a successful IT professional with data skills.
The second objective is to learn about different types of data, including structured and unstructured data.
The third objective is to be able to demonstrate your knowledge of at least two types of data storage: online and offline.
The fourth objective is to be able to describe how a client can access information from various sources through technology such as social media or the web. CompTIA DA0-001 exam dumps he best way to prepare for the exams.
The fifth objective is for you to be able to apply concepts related to using software applications such as Microsoft Office suite, Google Docs, and Adobe Creative Cloud.
CompTIA DA0-001 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Concepts and Environments | 15% | - Data storage systems: databases, data marts, warehouses, data lakes - Data types, structures, and formats - Data schemas, dimensions, and attributes - Structured, semi-structured, and unstructured data |
| Topic 2: Visualization and Reporting | 23% | - Building dashboards and reports - Design principles and best practices - Selecting appropriate visualizations and charts - Communicating insights and recommendations |
| Topic 3: Data Analysis | 23% | - Statistical methods: correlation, regression, hypothesis testing - Descriptive and inferential statistics - Interpreting results and identifying patterns/anomalies - Analytical techniques: trend, performance, exploratory, comparative |
| Topic 4: Data Mining | 25% | - Data profiling, cleansing, and validation - Data acquisition and integration methods - Querying and retrieving data - Data transformation, manipulation, and enrichment |
| Topic 5: Data Governance, Quality and Controls | 14% | - Data lifecycle management and controls - Data governance frameworks and policies - Data privacy, security, and compliance - Data quality standards and measurement |
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