DA0-002 · ● Active · Associate · CompTIA
Vendor-neutral entry-level certification validating foundational data analytics, data quality, and visualization skills. Launched October 14, 2025. Replaces DA0-001 (retiring April 14, 2026).
Exam facts
| Field | Value |
|---|---|
| Cost | USD $255 (standard); $304 with 1 retake voucher |
| Duration | 90 minutes |
| Questions | 90 max (mix of multiple choice and performance-based) |
| Passing | 675/900 scaled score |
| Format | Multiple choice + performance-based questions (PBQs) + drag-drop |
| Delivery | Pearson VUE (online proctored or test center) |
| Languages | English (primary); Japanese and Thai available |
| Valid | 3 years |
| Renewal | CE credits or retake required |
| Prerequisites | 18–24 months data analyst or equivalent role experience recommended |
| Released | October 14, 2025 |
| Retiring | N/A (active through 2029+; predecessor DA0-001 retires April 14, 2026) |
Vendor source — CompTIA Data+ Certification ↗
Official exam guide — DA0-002 Exam Objectives (PDF) ↗
Exam blueprint — DA0-002 V2 Certification Exam Objectives ↗
About
CompTIA Data+ (DA0-002) is a vendor-neutral, associate-level certification validating foundational competencies in data concepts, data acquisition and preparation (ETL/ELT), statistical analysis, data visualization, and data governance. Launched October 14, 2025, it replaces the original DA0-001 (retiring April 14, 2026 in English). The new version expands coverage of cloud data environments, AI/ML concepts, modern BI tools, and data privacy frameworks (GDPR, PII handling). Designed for aspiring data analysts, BI analysts, and data quality specialists with 18–24 months of hands-on database and analytics experience.
Domain context — Data / AI
Data analytics and business intelligence at entry level. Core competencies: SQL querying, data wrangling, basic statistical literacy, dashboard design, data governance and privacy.
Read full deep dive — Data / AI / ML Domain →
Topics covered
Domain 1: Data Concepts and Environments
- Database types (relational, NoSQL, graph, time-series)
- Data formats (CSV, JSON, XML, Parquet, Avro)
- Data warehouses vs. data lakes vs. lakehouses
- Cloud data platforms (Snowflake, BigQuery, Redshift, Azure Synapse)
- Structured vs. unstructured data
Domain 2: Data Acquisition and Preparation
- ETL and ELT methodologies
- Data ingestion methods (APIs, web scraping, file uploads, streaming)
- Data cleaning and transformation
- Handling missing values and outliers
- Data quality assessment and validation
- Data lineage and metadata management
Domain 3: Data Analysis
- Descriptive statistics (mean, median, standard deviation, quartiles)
- Inferential statistics and hypothesis testing (p-values, significance)
- Exploratory data analysis (EDA)
- Trend analysis and forecasting basics
- Correlation and regression
- Segmentation and clustering concepts
Domain 4: Visualization and Reporting
- Dashboard design principles
- Chart types and when to use them (bar, line, scatter, heat map, etc.)
- Storytelling with data
- Report design and best practices
- Interactive visualization tools (Tableau, Power BI, Looker)
- Accessibility and clarity in visualizations
Domain 5: Data Governance, Quality, and Controls
- Data classification and PII/PHI protection
- Access control and authentication
- Data privacy regulations (GDPR, CCPA, HIPAA basics)
- Data quality metrics and monitoring
- Data stewardship and ownership
- Compliance and audit trails
Source: Official DA0-002 Exam Objectives ↗
Common skills at Data / AI · Associate
Shared competencies for data analysts at entry/associate level — not specific to this cert.
- SQL fundamentals — SELECT, WHERE, JOIN, GROUP BY, aggregate functions, window functions intro
- Data wrangling — Excel, Power Query, pandas (Python), spreadsheet formulas
- Descriptive statistics — mean, median, mode, variance, standard deviation, percentiles
- Visualization literacy — matching chart type to data/audience; color theory; accessibility
- ETL/ELT basics — understanding data pipelines, transformations, data flow
- Data quality — validation, profiling, handling null/missing data, outlier detection
- Business intelligence — KPIs, metrics, dashboard design, reporting for stakeholders
- Data governance fundamentals — PII, data classification, basic privacy (GDPR, CCPA concepts)
- Database basics — relational schema, normalization, indexes, simple query optimization
- BI tools familiarity — Tableau or Power BI user-level features (not advanced admin)
Recommended courses at Data / AI · Associate
| Provider | Title | Cost | URL |
|---|---|---|---|
| CompTIA (official) | CertMaster Learn: Data+ DA0-002 | $149 | ↗ |
| CBT Nuggets | CompTIA Data+ (DA0-002) Training | $99–119/mo | ↗ |
| Jason Dion (Udemy) | CompTIA Data+ Complete Course & Practice Exam | $11.99–$79.99 | ↗ |
| Pluralsight | CompTIA Data+ Path | $299/year or $29/mo | ↗ |
| LinkedIn Learning | CompTIA Data+ (DA0-002) Cert Prep | Included w/ Premium | ↗ |
| Udemy (multiple instructors) | Data+ DA0-002 courses | $10–$50 (frequent sales) | ↗ |
| Coursera | Data Analytics & Visualization (partnered) | Free audit / $39+ cert | ↗ |
Course-selection rule: Verify the course is specifically labeled DA0-002 or Data+ V2, not the older DA0-001 version.
Practice exams
| Provider | Title | Cost | URL |
|---|---|---|---|
| CertMaster Practice (CompTIA official) | CertMaster Practice: Data+ | $69 | ↗ |
| MeasureUp (CompTIA partner) | CompTIA Data+ DA0-002 Practice Exam | $59–$99 | ↗ |
| Boson | CompTIA Data+ Practice Exams | $75–$99 | ↗ |
| ExamTopics / CertPractice | Free/paid Data+ DA0-002 practice tests | Free / $20–$40 | ↗ |
Recommendation: Start with CertMaster Practice (official, aligned exactly with exam blueprint), then supplement with MeasureUp or Boson (realistic PBQ simulations).
Books
| Title | Author | Publisher | Year | ISBN | URL |
|---|---|---|---|---|---|
| CompTIA Data+ Study Guide: Exam DA0-002 | Mike Chapple, Sharif Nijim | Sybex | 2025 | 978-1394320912 | ↗ |
| CompTIA Data+ Study Guide: Exam DA0-002, 2nd Edition | Mike Chapple, Sharif Nijim | Wiley | 2025 | 978-1394320929 | ↗ |
Note: The Sybex/Wiley study guide includes 2 full practice exams and 1 year of online study environment access. Authors Chapple and Nijim are recognized CompTIA training developers with extensive security + data certifications background.
Typical job titles at Data / AI · Associate
Data Analyst · Junior Data Analyst · BI Analyst · Business Intelligence Analyst · Reporting Analyst · Data Quality Analyst · Junior Analytics Engineer
(Based on job postings requiring or preferring CompTIA Data+ certification, 2026.)
Salary
| Region | Range | Source |
|---|---|---|
| USD | $96,250–$138,500 (midpoint $117,250) | Robert Half 2026 ↗ · Glassdoor ↗ |
| ZAR | R305,517–R574,467 (midpoint ~R440,000) | PayScale ZA ↗ · SalaryExpert ↗ |
| GBP | £31,250–£47,500 (midpoint £40,000) | IT Jobs Watch ↗ · PayScale UK ↗ |
| EUR | €38,000–€55,000 (Western Europe avg) | Robert Walters Europe ↗ |
Note: Salaries vary by experience, location (London/NYC premium +15–25%), company size, and industry vertical. Certified candidates typically earn top-of-range for junior roles.
Skills validated
Concrete technologies and methodologies tested by DA0-002 — distinct from shared "Common skills" above.
- SQL querying — SELECT, JOIN (inner, left, right), GROUP BY, aggregate functions, subqueries, window functions intro
- Data transformation — ETL/ELT concepts, data cleaning, null handling, standardization
- Spreadsheet tools — Excel/Sheets: VLOOKUP, pivot tables, Power Query, INDEX/MATCH
- Statistical analysis — hypothesis testing, p-values, confidence intervals, correlation, basic regression
- Visualization platforms — Tableau Desktop, Microsoft Power BI Desktop, Google Looker (basics)
- BI reporting — KPI definition, metric design, dashboard layout, story-driven visuals
- Data governance — data classification, PII/PHI, GDPR compliance, access controls, audit trails
- Database concepts — relational schema design, normalization, indexing, query optimization basics
- APIs and data ingestion — REST API calls, JSON parsing, web scraping concepts, file-based ingestion
- Data quality tools — data profiling, validation rules, anomaly detection, quality metrics
- Python or R intro — basic data manipulation with pandas (Python) or base R
- Cloud data platforms — familiarity with Snowflake, BigQuery, Azure Synapse, AWS Redshift concepts
Related certifications
- Stacks with: CompTIA A+ (220-1101, 220-1102) ↗ · CompTIA Network+ (N10-008) ↗ (foundational IT pathway)
- Prerequisite for: AWS Certified Data Engineer – Associate (DEA-C01) ↗ · Snowflake SnowPro Core (COF-C03) ↗ · Microsoft DP-700 (Fabric Data Engineering Associate) ↗
- Equivalents at this level: Microsoft DP-900 (Azure Data Fundamentals) ↗ (foundational, broader scope) · Google Cloud Associate Cloud Engineer (ACE) ↗ (broader cloud role)
- Replaces: CompTIA Data+ DA0-001 (retired April 14, 2026 in English; July 16, 2026 in Japanese/Thai)
- Vendor overview: CompTIA Vendor Overview ↗
Sources
- CompTIA Data+ Certification (Official) ↗
- DA0-002 Exam Objectives PDF ↗
- DA0-002 V2 Blueprint (Koenig Solutions) ↗
- CompTIA Data+ V2 Retirement Info ↗
- CompTIA CertMaster Learn ↗
- CompTIA CertMaster Practice ↗
- CBT Nuggets Data+ Course ↗
- Jason Dion Udemy Course ↗
- MeasureUp Practice Exams ↗
- Boson Practice Exams ↗
- Sybex Study Guide (Chapple, Nijim) ↗
- Robert Half 2026 Salary Guide ↗
- Glassdoor Data Analyst Salary ↗
- PayScale ZA Data Analyst ↗
- IT Jobs Watch Data Analyst UK ↗
Last verified: 2026-05-01 Parent ecosystem: CompTIA Foundational & Data Certifications Parent domain: Data / AI / ML Domain Vendor overview: CompTIA Vendor Overview