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CompTIA certification

CompTIA Data+

The early-career certification for turning raw data into meaningful insights.CompTIA Data+ is an early-career data analytics certification that shows you have the practical skills to turn raw data into meaningful insights. Gain the confidence to analyze, interpret, and communicate data clearly, so you can solve real business problems, stand out to employers, and help your organization make smarter, data-driven decisions.
CompTIA
Exam version: V2
Target roleData analyst

Skills you'll

learn

Build skills with CompTIA learning and validate them with the CompTIA Data+ certification.
Build a foundation in modern data concepts so you can confidently navigate analytics tools and data sources in any organization.
Transform, clean, and organize raw data to make it reliable and useful for analysis.
Apply statistical methods to extract trends, uncover insights, and support business decisions.
Use data visualizations and dashboards to translate complex results into presentations anyone can understand.
Maintain data quality, ensure compliance, and protect sensitive information in alignment with industry standards.
Solve data problems, validate reports, and resolve analytics issues as they arise on the job.

Exam

details

Everything you need to know before taking the CompTIA Data+ exam.
Exam versionV2
Exam series codeDA0-002
Launch dateOctober 14, 2025
Number of questionsMaximum of 90 questions
Types of questionsMultiple-choice and performance-based
Duration90 minutes
Passing score675 (on a scale of 100–900)
LanguagesEnglish and Japanese
Recommended experience18–24 months in a data analyst or similar job role, with exposure to databases, analytical tools, basic statistics, and data visualization
RetirementUsually three years after launch (estimated 2028)
Accreditation and benefitsISO accredited by the ANSI National Accreditation Board (ANAB), and mapped to the NICE Framework Data Analyst (IO-WRL-001) work role.

Exam

objectives

The CompTIA Data+ (V2) exam covers the following domains, weighted by their share of the exam.
1

Data concepts and environments

20%
  • Explain data concepts: database types, data structures, file extensions, and data types.
  • Identify data sources: databases, APIs, website data, files, logs and repositories.
  • Recognize infrastructure concepts: cloud, on-premise, storage, and containerization.
  • Identify data tools: coding environments, BI software, and analysis platforms.
  • Understand AI concepts: identify AI models, natural language processing, and robotic automation.
2

Data acquisition and preparation

22%
  • Use data acquisition methods: data integration and queries to gather and combine data.
  • Perform data exploration: find missing values, duplication, redundancy, or outliers.
  • Apply data transformation: cleansing, merging, parsing, and formatting data.
3

Data analysis

24%
  • Communicate analysis results: select methods for different audiences.
  • Select statistical methods: apply basic statistical techniques to data.
  • Troubleshoot analysis issues: use tools and resources to resolve problems.
4

Visualization and reporting

20%
  • Create effective visuals: use charts, maps, tables, and design elements.
  • Deliver reports: provide dashboards or summaries using appropriate methods.
  • Validate reporting accuracy: apply validation and review to solve reporting issues.
5

Data governance

14%
  • Explain data management practices: documentation, versioning, and data lineage.
  • Summarize compliance requirements: retention, audits, and regulations.
  • Compare privacy and protection strategies: access control, encryption, and masking.
  • Implement quality assurance: profiling, monitoring, and testing for data quality.
Exam information is published by CompTIA and may change. Contact us for the current exam version and available sessions.

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