CompTIA Data+ (DA0‑002) Practice Exams
About the CompTIA Data+ DA0-002 exam
Exam at a glance
CompTIA's vendor-neutral data analyst certification at the intermediate tier.
Domain weighting
- Data Concepts and Environments: ~15%
- Data Mining: ~24%
- Data Analysis: ~24%
- Visualization: ~21%
- Data Governance, Quality, and Controls: ~16%
Who it's for
DA0-002 (released 2024, replacing DA0-001) targets data analysts, junior business intelligence professionals, and IT professionals transitioning into analytics roles. Because it's vendor-neutral, the same certificate maps onto Excel, SQL, Tableau, Power BI, Python, and R ecosystems — useful when your day-job stack changes or you're moving between employers.
Prerequisites
No formal prereqs. CompTIA recommends 18–24 months of experience in a report or business-analyst role before sitting the exam. Candidates with shorter tenure can still pass with focused preparation, but the scenario-based items reward day-to-day exposure to messy real-world data.
Why take this certification
- Vendor-neutral signal. Unlike a Tableau- or Power BI-specific badge, Data+ proves portable analyst fundamentals — recruiters and hiring managers can read it without knowing your exact tool stack.
- Bridge from IT or business roles into analytics. If you're moving from helpdesk, ops, marketing, or finance into a data-analyst role, Data+ gives you a structured curriculum and a credential hiring managers can verify on a resume.
- Foundation for the CompTIA data track. Data+ is the on-ramp to DataSys+ (DS0-001) for systems-side work and DataAI+ (DY0-001) for AI-augmented analytics.
- Practical, tool-agnostic skills. The blueprint focuses on judgment — picking the right chart, choosing the right central-tendency measure, spotting data-quality problems — rather than menu paths in a specific product. That portability survives tool changes.
What you'll learn in the DA0-002 exam
DA0-002 validates that you can take a business question, find the right data, clean it, analyze it, visualize the result, and respect the governance rules that apply along the way. The exam is scenario-driven — most items describe a workplace situation (a stakeholder, a dataset, a deadline) and ask which step or technique applies.
Core topic areas
- Data fundamentals: data types and formats, structured vs semi-structured vs unstructured data, common schemas (star, snowflake), file formats (CSV, JSON, Parquet), and database vs warehouse vs lake.
- Data acquisition: SQL queries (joins, aggregates, window functions at concept level), API consumption, file imports, web scraping basics, and the trade-offs between each.
- Data cleaning: handling nulls, duplicates, outliers, type conversions, and standardizing free-text fields. Core ETL/ELT concepts and when each pattern fits.
- Statistical analysis: descriptive statistics (mean, median, mode, standard deviation, quartiles), correlation vs causation, hypothesis-testing basics, p-values at concept level, and the sample-vs-population distinction.
- Visualization: chart selection (bar, line, scatter, histogram, heatmap, box plot, pie — and when not to use pie), color and accessibility considerations, dashboard design principles, and storytelling-with-data narrative structure.
- Data governance: privacy regulations at concept level (GDPR, HIPAA, PCI-DSS, US state laws), data-quality dimensions (completeness, accuracy, consistency, timeliness, validity, uniqueness), the data lifecycle (acquisition → retention → archive → destruction), and classification schemes.
Analytical patterns you'll need to recognize
- Choosing the right central-tendency measure when data is skewed (mean vs median).
- Picking a chart that matches your data shape and audience — bar for categorical comparison, line for time series, scatter for correlation, histogram for distribution.
- Spotting data-quality issues from descriptive stats alone (impossible values, suspicious nulls, unexpected variance).
- Reading a query plan or join diagram and predicting cardinality issues before they bite.
- Applying governance controls — masking, anonymization, role-based access — to a scenario where PII or PHI appears.
How the practice exams help
Each free question and every premium exam mirrors the scenario-style format CompTIA uses — short business stem, four to six plausible options, one or two correct. Detailed explanations cover not just why the right answer is right but why the distractors are wrong, so you learn analyst judgment rather than memorizing answers.
How to prepare for the DA0-002 exam
A successful Data+ preparation strategy combines blueprint study, hands-on data work, and exam simulation. Recommended approach:
- Study the official blueprint (2–3 weeks). Work through CompTIA CertMaster Learn + Practice or the official DA0-002 Study Guide. Take notes on the five domains — Data Concepts, Data Mining, Data Analysis, Visualization, Governance — and flag the topics you're weakest on for round 2.
- Hands-on data work (2–4 weeks). Theory alone won't get you across the line. Pick a public dataset (Kaggle, data.gov, your own work data with permission) and work end-to-end: load, clean, analyze, visualize. Free Kaggle courses cover Python, pandas, and visualization at exactly the depth Data+ tests.
- SQL and spreadsheet drills (1 week). Run through SQLZoo or LeetCode SQL until joins, aggregates, and subqueries feel automatic. Practice pivot tables, lookup functions, and basic statistical formulas in Excel or Google Sheets.
- Practice exams (1–2 weeks). Take timed practice tests to identify weak domains. Detailed explanations on every answer option help you learn the reasoning, not just memorize answers. Aim for consistent 80%+ scores before scheduling your exam.
Recommended timeline
6–10 weeks of focused study (8–12 hours per week) for professionals with some analyst or reporting experience. Career changers with no prior data work should allow 10–14 weeks.
Official resources
Start with the official CompTIA Data+ exam page for the current blueprint and sample questions. CompTIA CertMaster Learn + Practice is the publisher-aligned curriculum if you want a guided path; the official DA0-002 Study Guide works well for self-paced learners who prefer reading.
Frequently asked questions
Are these actual exam questions?
No. All Nex Arc CompTIA Data+ DA0-002 practice questions are original content based on the provider's published exam blueprint, official documentation, and real-world scenarios across every topic the exam covers. We do not offer brain dumps, leaked questions, or actual exam content. Using or distributing real exam questions violates certification provider agreements and can result in certification revocation.
How many questions are in the CompTIA Data+ DA0-002 exam?
DA0-002 contains a maximum of 90 questions delivered in 90 minutes. Items are a mix of multiple-choice (single and multiple response) and performance-based questions that require you to apply analysis steps in a simulated environment.
What's the DA0-002 passing score?
The passing score is 675 on a scaled 100–900 range. CompTIA does not publish a fixed percentage cutoff because the scale is normalized across exam forms — focus on consistent topic mastery rather than a target percent on practice tests.
How do I access the full Data+ practice exam?
Click on the Buy Now button in the sidebar to purchase the complete CompTIA Data+ course. After payment, you'll have instant access to 12 practice exams with detailed explanations and lifetime access.
What are the prerequisites for the Data+ exam?
There are no formal prerequisites for DA0-002. CompTIA recommends 18–24 months of experience in a report/business analyst role, working with basic SQL, spreadsheets, and visualization tools. Candidates transitioning from adjacent IT or analytics-curious business roles can prepare in 6–10 weeks with structured study; deeper statistical or programming background shortens that further but is not required.
How long is the Data+ certification valid?
CompTIA Data+ is valid for three years from the date you pass DA0-002. Renewal happens through CompTIA's Continuing Education (CE) program — you submit qualifying activities (training, higher-tier certs, work experience, conference attendance) to earn 20 CEUs over the three-year cycle, plus the annual CE fee. Alternatively, you can retake the current version of the exam to reset the three-year clock without CEU submissions.
What's the exam cost and can I retake it if I fail?
DA0-002 lists at $269 USD globally (converted to local currency). The exam is delivered through Pearson VUE at testing centers or via online proctoring. If you fail your first attempt you can retake immediately with no waiting period; from the third attempt onward CompTIA requires a 14-day wait between tries. Each attempt requires a new $269 payment. CompTIA discount vouchers and academic/employee bundles can reduce the per-attempt cost.
Which tools and platforms does Data+ cover?
Data+ is intentionally vendor-neutral. The blueprint covers concepts that apply across the analyst toolchain: SQL (any dialect), spreadsheets (Excel / Google Sheets), BI/visualization platforms (Tableau, Power BI, Looker, Qlik), and scripting environments (Python with pandas, R). You won't be asked about Tableau-specific menus or Power BI ribbon paths — questions focus on portable concepts like join types, chart selection, descriptive statistics, and data-quality controls that transfer between every major tool.
How does Data+ DA0-002 differ from DataSys+ and DataAI+?
All three are CompTIA's data-track certifications but target different roles. Data+ (DA0-002) is the analyst foundation — querying, cleaning, statistics, visualization, and governance for business analysts. DataSys+ (DS0-001) targets data-systems administrators — building and operating databases, ETL pipelines, and data infrastructure. DataAI+ (DY0-001) is the newest, focused on AI-augmented analytics — using generative AI and machine learning to accelerate analysis and prompt-engineer for data workflows. Most candidates start with Data+ and add DataSys+ or DataAI+ based on their career direction.
What changed between DA0-001 and DA0-002?
DA0-002 (released 2024) replaces the retiring DA0-001. The new version restructures the blueprint into five domains, expands coverage of modern visualization patterns and storytelling, adds more performance-based items, and updates governance content to reflect current privacy regulations like GDPR and US state-level privacy laws. If you're studying now, target DA0-002 — DA0-001 is being phased out by CompTIA and DA0-002 is the only version newly-certified candidates should pursue.