DA0-002 Real Exam Questions
CompTIA Data+ Certification Exam. Everything you need to prepare, practice, and pass.
124
Questions
6
Exam Domains
Included
Explanations
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Certification Overview
The exam tests breadth across the data stack: SQL fundamentals and query construction, data types and quality validation, ETL/data preparation workflows, business intelligence principles, and foundational data governance. Expect practical scenarios where you apply visualization best practices, ensure data integrity, and recommend solutions for real-world data challenges.
What This Certification Proves
The CompTIA Data+ certification validates foundational knowledge across the complete data lifecycle—from acquisition and preparation through analysis, visualization, and governance. This entry-level credential proves you understand data concepts, SQL basics, data quality principles, and how to communicate data insights to business stakeholders.
Who Should Take This Exam
Career changers entering data roles, business analysts aspiring to analytics, IT professionals moving toward data work, or recent graduates with 0-2 years of experience. No formal prerequisites required, but comfort with spreadsheets and basic IT concepts helpful.
Topic Breakdown
6 domains covering 124 questions
| Domain | Questions | Weight |
|---|---|---|
| Data Acquisition And Preparation | 35 | 28% |
| Visualization And Reporting | 34 | 27% |
| Data Concepts And Environments | 27 | 22% |
| Data Analysis | 15 | 12% |
| Data Governance | 11 | 9% |
| Virtualization And Cloud Computing | 2 | 2% |
Study Plans
Choose a study plan that matches your schedule and experience level
30 Days
Intensive Sprint
Week 1-2
- Master fundamentals: Data Acquisition And Preparation
- Read CompTIA official documentation
- Complete 5 questions daily
Week 3
- Deep dive: Visualization And Reporting
- Review weak areas from results
- Take 2 full-length exams
Week 4
- Review all flagged questions
- Timed exams to build stamina
- Final revision of key concepts
60 Days
Balanced Approach
Week 1-2
- Survey all exam domains
- Set up study environment
- Begin with foundational topics
Week 3-4
- Focus: Data Acquisition And Preparation
- Focus: Visualization And Reporting
- 3 questions daily
Week 5-6
- Focus: Data Concepts And Environments
- Hands-on labs if applicable
- Review explanations for wrong answers
Week 7-8
- Complete all 124 questions
- Identify and eliminate weak areas
- Take 3 full-length timed tests
90 Days
Comprehensive Study
Month 1
- Learn all exam domains at a comfortable pace
- Build strong foundational knowledge
- 2 questions daily
Month 2
- Deep dive into each domain
- Hands-on practice and labs
- Take weekly timed exams
Month 3
- Work through all 124 questions
- Identify and eliminate weak areas
- Take 3 full-length timed exams
DA0-002-Specific Tips
- Build SQL fluency early—practice basic SELECT, WHERE, JOIN queries on real datasets daily; SQL appears across multiple domains
- Master data quality concepts (validation, profiling, completeness, accuracy) as they're foundational to the data preparation domain
- Learn one visualization tool hands-on (Tableau or Power BI)—don't just study theory; create dashboards to cement principles
- Focus on data governance basics: understand metadata, data dictionaries, data lineage, and why governance matters to compliance
- Practice identifying data types and their limitations—questions test whether you know when to use categorical vs. numerical vs. date fields
- Distinguish between data collection methods and their trade-offs (APIs, sensors, surveys, logs)—key to the acquisition domain
- Take practice exams frequently (aim for 70+ of your 124 available questions) to identify weak domains and build test-taking confidence
Relevant Career Roles
Sample Questions
Try 5 free questions from the DA0-002 question bank
An analyst needs to produce a final dataset using the following tables: The expected output should be formatted as follows: | CourseID | SectionNumber | StudentID | FirstName | LastName | Which of the following actions is the best way to produce the requested output?
A data analyst needs to identify outliers from a given dataset. Which of the following visualizations is the best way to identify outliers?
A data analyst is joining two tables with different content and one common field. Which of the following should the analyst do to most efficiently meet this requirement?
A developer builds an online survey that requires all questions to have an answer. Which of the following inconsistencies does this setting prevent?
A data analyst needs to remove all duplicate values between two tables, "Employees" and "Managers," using SQL SELECT statements. Which of the following should the analyst use for this task?
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