CompTIA · DA0-001
CompTIA Data+ validates the skills required to transform business requirements into data-driven decisions by mining, manipulating, and analyzing complex datasets. It covers the full data lifecycle including statistical methods, visualization, and data governance and quality standards.
Questions
700
Duration
90 minutes
Passing Score
675/900
Difficulty
AssociateLast Updated
Mar 2026
Use this DA0-001 practice exam to prepare for CompTIA Data+ (DA0-001) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 700 questions for CompTIA DA0-001, so you can review the exam steadily instead of relying on one long cram session.
As you practice, pay extra attention to recurring topics such as Data Concepts and Environments, Data Mining, Data Analysis, Visualization, and Data Governance, Quality, and Controls. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.
The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.
CompTIA Data+ (DA0-001) is an entry-level, vendor-neutral certification that validates the ability to analyze, interpret, and communicate business data effectively. The certification proves competency in transforming business requirements into data-driven decisions through data mining, manipulation, and analysis of complex datasets. It covers the full data lifecycle, including statistical methods, data visualization, and governance and quality standards. This certification is uniquely positioned as the only entry-level, hands-on analytics certification that does not focus on a single vendor's tools, making it accessible to professionals transitioning into data analytics roles.
CompTIA Data+ targets early-career professionals seeking to advance into data analytics roles. Ideal candidates include business analysts, report developers, and professionals with 18-24 months of experience in roles involving data analysis, reporting, or business analytics. The certification is also suitable for career changers with basic analytics exposure, IT professionals transitioning to data roles, and individuals with fundamental understanding of statistics and data visualization who want formal credential validation.
While CompTIA Data+ has no formal prerequisites, the certification is designed for candidates with 18-24 months of practical experience in a report, business analyst, or similar analytical role. Recommended prerequisite knowledge includes exposure to databases and analytical tools, a basic understanding of statistics and probability, and hands-on experience with data visualization tools. Familiarity with spreadsheet applications (Excel) and SQL concepts is beneficial, though not mandatory. Candidates should have some exposure to business analytics workflows and report creation.
The CompTIA Data+ exam (DA0-001) consists of a maximum of 90 scored questions, combining multiple-choice (single and multiple response) and performance-based question (PBQ) types. The exam is delivered online or in-person at Pearson VUE testing centers and must be completed within 90 minutes. Performance-based questions require hands-on skills such as dataset manipulation, drag-and-drop interactions, and scenario analysis. The exam uses scaled scoring on a scale of 100-900 points, with a passing score of 675. Non-native English speakers may be eligible for extra testing time, and ADA accommodations are available with proper documentation.
CompTIA Data+ certification significantly enhances employability in the rapidly growing data analytics field. Certified professionals qualify for roles including Data Analyst, Business Analyst, Business Intelligence Specialist, Marketing Analyst, and reporting specialists. The current job market shows over 193,000 U.S. job postings seeking data analysis, data mining, and data visualization skills, with many entry-level positions available. Salary expectations range from $45,600 for junior professionals to $95,200+ for experienced analysts, with experienced senior data professionals earning $110,000 or more. As a vendor-neutral credential, Data+ is recognized across industries and demonstrates data literacy—a critical skill for career advancement and mobility in today's data-driven economy. The certification differentiates candidates in competitive job markets and serves as a foundation for advancing to more specialized certifications or senior analytics roles.
5 sample questions with answers and explanations. Start a practice session to test yourself across all 700 questions.
Preview — answers shown1. Adatum's analytics team calculates a Pearson correlation coefficient of r = 0.82 between advertising spend and monthly revenue. Which conclusion is most accurate? (Select one!)
Explanation
A Pearson correlation coefficient of r = 0.82 indicates a strong positive linear relationship (values above 0.7 are generally considered strong). However, correlation does not imply causation — a third confounding variable could explain both, or the relationship could be coincidental. R-squared (r²), not r itself, represents the proportion of variance explained (0.82² = 0.67, or 67%). The correlation coefficient does not represent the slope of the relationship or the rate of change.
2. Tailspin Toys is preparing a dashboard for the executive leadership team showing annual revenue performance against targets by business unit. The executives typically spend less than two minutes reviewing dashboards and need to quickly identify which units are underperforming. Which design approach is most appropriate for this audience? (Select one!)
Explanation
C-suite executives require high-level summaries that enable fast decision-making with minimal cognitive load. KPI cards showing performance metrics alongside RAG (Red, Amber, Green) status indicators allow executives to instantly identify which business units are off-target, at risk, or performing well. Sparklines provide trend context within a compact format. Detailed transactional tables require too much time to interpret and present information irrelevant to executive-level decision-making. Interactive scatter plots require analytical interpretation that is more appropriate for data analysts. A multi-tab workbook adds complexity and assumes executives want to explore data independently, which contradicts the observed two-minute review pattern.
3. A data analyst at Northwind Traders is designing a data warehouse for retail sales reporting. The schema has a central Sales fact table connected to separate Product, Customer, Date, and Store dimension tables. Each dimension table is fully denormalized. What type of schema is being used? (Select one!)
Explanation
A star schema consists of a central fact table surrounded by fully denormalized dimension tables, creating a shape that resembles a star. The dimension tables in a star schema are not broken down further into sub-dimension tables, which reduces the number of joins required for queries and improves read performance. A snowflake schema would have normalized dimension tables that link to additional sub-dimension tables, creating more complex joins. Third normal form describes a database normalization level used in OLTP systems to reduce redundancy, not a warehouse schema pattern. Entity-relationship schema describes a conceptual modeling approach, not a warehouse design pattern.
4. Adatum's privacy officer must classify sensitive data elements to ensure regulatory compliance. Which three data elements match their correct regulatory classification? (Select three!)
Multiple correct answersExplanation
PII (Personally Identifiable Information) includes identifiers like Social Security numbers and passport numbers that can uniquely identify individuals, protected under various privacy laws including GDPR and CCPA. PHI (Protected Health Information) refers to health-related information regulated under HIPAA including diagnoses, prescriptions, and insurance claims. PCI data covers payment card information including card numbers, CVV codes, and cardholder details subject to PCI DSS standards. Employee department names and inventory data are general business information not covered by these specific frameworks.
5. Adatum's dashboard development project is behind schedule. The analyst has completed a detailed wireframe showing layout, KPIs, and filter placements. The project manager wants to skip directly to development to save time. What is the correct next step according to standard dashboard development process? (Select one!)
Explanation
The standard dashboard development process follows this sequence: Wireframe, then Stakeholder Approval, then Develop, then Deploy to Production. Obtaining stakeholder approval after wireframing is critical because changes to a wireframe take minutes while reworking developed functionality takes days. Skipping approval risks building the wrong solution and causes more delay than the approval step itself. Deploying to production without stakeholder review puts an unvalidated, potentially incorrect dashboard in front of end users. While technical specifications may be useful, the stakeholder approval of the wireframe design and functionality should come before additional technical documentation to ensure the team is building what is actually needed.
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