CompTIA Data+ (DA0-002) Exam Preparation Course

Prepare for the CompTIA Data+ DA0-002 Exam

Develop the practical analytical skills required to transform raw data into useful business insights with this CompTIA Data+ DA0-002 exam preparation course. The course covers data collection, preparation, analysis, visualization, reporting, governance and quality management.

CompTIA Data+ is a vendor-neutral certification created for professionals who interpret data, create reports and support data-driven decisions. DA0-002 is the current Data+ exam version and includes modern topics such as cloud data environments, artificial intelligence concepts, data privacy and automated reporting.

Explore more professional training through our IT Certifications course category, browse all available online courses or review our study guides.

About the DA0-002 Exam

The CompTIA Data+ DA0-002 exam contains a maximum of 90 questions and allows 90 minutes for completion. Candidates may encounter multiple-choice and performance-based questions.

CompTIA recommends approximately 18–24 months of experience in a data analyst or similar role. Candidates should also have some exposure to databases, analytical tools, basic statistics and data visualization.

The examination validates your ability to:

• Interpret and manipulate data

• Translate business requirements into analytical tasks

• Collect, clean and prepare datasets

• Apply basic statistical methods

• Analyze data for patterns and trends

• Build meaningful visualizations and reports

• Troubleshoot data and reporting problems

• Apply governance, quality, privacy and security controls

Before scheduling the examination, candidates should confirm current requirements through the official CompTIA Data+ certification page.

Score and Pass Mark

The required passing score for the CompTIA Data+ DA0-002 examination is 675 on a scale of 100–900.

This is a scaled score rather than a direct percentage. CompTIA does not publish the precise number of questions a candidate must answer correctly, and different questions may contribute differently to the final result.

With up to 90 questions in 90 minutes, effective time management is important. Performance-based questions can require additional time because they test your ability to work through realistic analytical tasks.

This course provides timed quizzes, performance-based exercises and five full-length mock examinations to improve your accuracy, analytical reasoning and exam pacing.

The official certification is awarded only after passing the authorized DA0-002 examination. Candidates can schedule the exam through the CompTIA Pearson VUE testing portal.

DA0-002 Exam Domains

Data Concepts and Environments — 20%

Build a strong foundation in modern data terminology, structures and environments. You will learn how data is created, classified, stored and accessed across different systems.

Topics include:

• Structured, semi-structured and unstructured data

• Numeric, string, Boolean, date, time and multimedia data

• Relational and non-relational databases

• Tables, records, fields, keys and schemas

• CSV, JSON, XML and spreadsheet files

• Data warehouses, data marts and data lakes

• OLTP and OLAP systems

• On-premises, cloud and hybrid environments

• Object, file and block storage

• Analytical notebooks and business-intelligence tools

• Artificial intelligence and machine-learning concepts

• Natural language processing and automated reporting

This section helps you identify the most suitable data environment, storage method or analytical tool for a given business requirement.

Data Acquisition and Preparation — 22%

Learn how analysts collect, combine, profile, clean and transform data before analysis. This domain emphasizes the importance of reliable data preparation.

Topics include:

• Databases, APIs, websites, files and application logs

• SQL filtering, grouping, aggregation and sorting

• Joins, unions and nested queries

• ETL and ELT processes

• Data profiling and exploration

• Missing and incomplete values

• Duplicate and redundant records

• Outliers and inconsistent formats

• Data validation

• Parsing and string manipulation

• Data-type conversion

• Binning, scaling and standardization

• Merging, appending and reshaping data

• Derived fields and calculated values

Applied exercises help you identify data-quality problems and select the most appropriate cleaning or transformation method.

Data Analysis — 24%

This is the largest DA0-002 domain. It assesses your ability to select suitable analytical methods, apply common functions and communicate findings to different audiences.

You will study:

• Descriptive analysis

• Inferential analysis

• Predictive analysis

• Prescriptive analysis

• Mean, median and mode

• Range, variance and standard deviation

• Percentages, ratios and rates

• Trends, patterns and correlations

• Logical, mathematical, date and string functions

• Key performance indicators

• Business and technical requirements

• Analytical assumptions and limitations

• Data validation

• Root-cause analysis

• SQL and connectivity troubleshooting

• Corrupted or incomplete data

• Logging and error investigation

The course focuses on selecting the correct method, interpreting the result and explaining its business meaning.

Visualization and Reporting — 20%

Learn how to present complex information clearly through reports, charts and dashboards. Effective visualization helps stakeholders understand results and make informed decisions.

Topics include:

• Bar, line, pie and area charts

• Scatterplots and histograms

• Maps and geographic visualizations

• Pivot tables

• Infographics

• Static and interactive dashboards

• Executive summaries

• KPI reports

• Labels, legends and color schemes

• Accessibility considerations

• Real-time and snapshot reporting

• Scheduled and ad hoc reports

• Dashboard filters

• Report validation

• Refresh and loading problems

• Data storytelling for different audiences

You will practise selecting the correct visual for trends, comparisons, distributions, relationships and geographic data.

Data Governance — 14%

Understand how organizations manage data responsibly throughout its lifecycle. This section covers documentation, privacy, security, compliance, ethics and data quality.

Topics include:

• Data ownership and stewardship

• Data dictionaries and metadata

• Data lineage and flow diagrams

• Sources of truth

• Versioning and refresh intervals

• Data retention and destruction

• Data classification

• Privacy and regulatory requirements

• Personally identifiable information

• Personal health information

• Role-based access control

• Encryption at rest and in transit

• Data masking and anonymization

• Ethical data use

• Audit requirements

• Incident reporting

• Quality assurance and user-acceptance testing

• Data health checks and automated monitoring

These principles help protect sensitive information while ensuring that analytical results remain trustworthy and reproducible.

Performance-Based Question Preparation

Performance-based questions require candidates to apply data knowledge to practical situations. You may need to interpret a dataset, correct a data-quality problem, choose an SQL operation, analyze statistical results or select the best visualization.

The course includes practical exercises involving:

• Profiling and cleaning datasets

• Identifying missing values and duplicates

• Selecting SQL joins and query operations

• Building ETL and ELT workflows

• Calculating statistical measures

• Interpreting correlations and distributions

• Choosing suitable charts

• Reviewing dashboards and KPIs

• Troubleshooting inaccurate reports

• Applying governance and privacy controls

These exercises build the analytical reasoning required for performance-based and scenario-driven multiple-choice questions.

Who Should Enrol?

This course is suitable for:

• Aspiring data analysts

• Junior business-intelligence analysts

• Reporting analysts

• Business and systems analysts

• Operations analysts

• Marketing analysts

• Financial analysts

• Database support professionals

• IT professionals working with reports

• Professionals transitioning into data analytics

Candidates who need broader technology foundations can begin with CompTIA Tech+ FC0-U71. Learners interested in data infrastructure may also explore Cloud+ CV0-004, Network+ N10-009 or Security+ SY0-701.

Work Opportunities After Completing This Course

The knowledge developed through this course can support applications for entry-level and supporting positions such as:

• Junior Data Analyst

• Reporting Analyst

• Business Intelligence Assistant

• Operations Analyst

• Marketing Data Analyst

• Sales Reporting Analyst

• Data Quality Analyst

• Business Analyst

• Data Governance Assistant

• Junior Database Reporting Specialist

Existing professionals may use these skills to improve reporting, measure performance, automate routine analysis and support evidence-based decision-making.

The O*NET Business Intelligence Analysts profile provides further information about common analytical tasks, technologies and workplace skills. Candidates can also review the U.S. Bureau of Labor Statistics Data Scientists profile when exploring longer-term data career pathways.

Completing this preparation course does not award the official CompTIA Data+ certification or guarantee employment. Certification requires passing the authorized DA0-002 exam. Employment eligibility depends on experience, education, technical ability, location and individual employer requirements.

Prepare, Practise and Track Your Progress

Begin with domain-specific quizzes before attempting the timed full-length mock examinations. Detailed explanations show why each answer is correct and why the alternatives are less suitable.

Performance reports, revision plans and readiness checklists help you identify weak domains and direct your final preparation toward the areas requiring the most attention.

Learn more about the training process through our How It Works page or contact AIProctoredExams for course assistance.

CompTIA and Data+ are trademarks of CompTIA, Inc. AIProctoredExams is not affiliated with or endorsed by CompTIA. This is an independent exam-preparation course.