CompTIA Data+ Certification Exam
Exam Code: DA0-001
The CompTIA Data+ (DA0-001) certification validates foundational data analytics skills needed to collect, analyze, visualize, and communicate data-driven insights. Offered by CompTIA, DA0-002 is the updated version of Data+, aligned with modern analytics practices, governance, and business reporting across industries.
- Exam Breakdown
- Domain Breakdown
- Access Breakdown
Exam Format
- Exam Code: DA0-001
- Certification Level: Associate / Intermediate
- Exam Duration: 90 minutes
- Passing Score: 675 (on a scale of 100–900)
- Unscored Content: The exam may include unscored questions for research purposes. These do not affect your score and are not identified. Time is adjusted accordingly.
Exam Details
- Question Types: Multiple choice and performance-based questions
- Number of Questions: Maximum of 90 questions
- Hands-On Questions: Performance-based items assess practical data analysis and interpretation skills.
Exam Policies
- Offline Proctoring: Must be rescheduled or canceled at least 48 hours before the scheduled exam time.
- Online Proctoring: Must be rescheduled or canceled at least 24 hours before the scheduled exam time (OnVUE policies apply).
- Waiting Period:
- First and second attempts: No waiting period
- Third attempt: 14 calendar days wait
- Retake Fee: Full exam fee must be paid for each retake.
Certification Validity and Renewal
- Validity: 3 years
- Renewal Options:
- Earn 30 Continuing Education Units (CEUs)
- Pass a higher-level CompTIA certification
- Retake the Data+ exam
Exam Fee
- Base Fee: $246 USD (excluding taxes)
- Taxes: Country-specific VAT/GST may apply
- Example: In India, 18% GST applies → $290.28 USD ($246 + $44.28 tax)
Prerequisites
- There are no mandatory prerequisites, but CompTIA recommends:
- 18–24 months of experience in a data analyst or business intelligence role
- Knowledge of:
- Microsoft Excel
- SQL
- Basic statistics
- Familiarity with data visualization tools
Exam Topics
- Data Concepts & Environments: Data types, structures, quality
- Data Mining: Collection, cleansing, transformation
- Data Analysis: Statistical methods, trend analysis
- Visualization: Dashboards, reports, storytelling
- Data Governance & Quality: Compliance, ethics, security
- For a detailed breakdown and official study guide, feel free to contact us!
Intended Audience
The Data+ certification is ideal for professionals in roles such as:
- Data Analyst
- Business Intelligence Analyst
- Reporting Analyst
- Operations Analyst
- Junior Data Scientist
Career Impact
Jobs You Can Get:
- Data Analyst
- Business Analyst
- Reporting Specialist
- Data Consultant
Average Salary:
- USA: $65,000 – $105,000
- India: ₹5,00,000 – ₹14,00,000
- UK: £35,000 – £65,000
- UAE: 140,000 – 260,000 AED
Why It’s Valuable:
- Vendor-neutral analytics certification
- Focus on practical data skills
- High demand in data-driven industries
- Strong foundation for advanced analytics roles
Exam Mode
The exam is proctored and can be taken either:
- In-person at authorized Pearson VUE test centres
- Online through OnVUE remote proctoring
Exam Booking Link
- Book your CompTIA Data+ Exam via Pearson VUE:
https://home.pearsonvue.com/comptia
Once you pass the exam:
- Download your certificate from CompTIA Certification Account
- Processing Time: 24–48 hours
- Access digital badge via Credly
Offers
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Top Reasons to Choose
CompTIA Data+ Certification Exam
Strong Demand for Data Analytics Skills
Organizations need professionals who can clean, analyze, visualize, and explain data. Data+ helps candidates build practical analytics skills used in reporting, dashboards, business intelligence, and decision-making roles.
Vendor-Neutral and Career-Focused Certification
CompTIA Data+ is not limited to one platform. It validates broad analytics knowledge across databases, tools, statistics, visualization, governance, and reporting, making it useful across many industries.
Good Foundation for Data Career Growth
This certification supports entry-level and early-career data roles while preparing candidates for advanced analytics, business intelligence, database, data governance, and AI-related learning paths in the future.
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FAQ
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Who should take the CompTIA Data+ DA0-002 exam?
The DA0-002 exam is ideal for early-career data professionals who analyze, interpret, and communicate business data. It suits data analysts, reporting analysts, business analysts, operations analysts, and professionals who work with databases, spreadsheets, dashboards, statistics, visualization tools, and data-driven decision-making in real business environments.
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How difficult is the CompTIA Data+ exam?
The CompTIA Data+ exam is considered moderate for candidates with basic analytics experience. It requires understanding data types, databases, statistics, cleaning, transformation, visualization, reporting, governance, and troubleshooting. Candidates without hands-on exposure may find performance-based and scenario-style questions challenging, so practical preparation is strongly recommended.
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Why does CompTIA offer the Data+ certification?
CompTIA offers Data+ to validate practical data analytics skills needed in modern organizations. Businesses rely on data for decisions, reporting, forecasting, and performance improvement. This certification helps employers identify candidates who can prepare data, analyze results, communicate insights, and follow governance and quality practices responsibly.
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What tools and resources can be used to prepare for Data+?
Candidates can prepare using official CompTIA exam objectives, CertMaster Learn, CertMaster Practice, study guides, practice tests, analytics labs, spreadsheet tools, SQL practice, visualization tools, and hands-on projects. Reviewing real datasets and practicing cleaning, analysis, charting, dashboards, and reporting can improve readiness for performance-based questions.
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Is the CompTIA Data+ certification still valuable in 2026?
Yes, CompTIA Data+ remains valuable in 2026 because organizations continue to need professionals who can translate raw data into useful business insights. The DA0-002 version includes updated coverage for modern data tools, cloud, AI-related concepts, governance, visualization, and analytics practices used in current workplaces.
