CompTIA Data+

Course subjects

Data concepts and environments

• Explain data concepts: Database types, data structures, file extensions, and data types.

• Identify data sources: Databases, APIs, website data, files, logs and repositories.

• Recognise infrastructure concepts: Cloud, on-premise, storage, and containerisation.

• Identify data tools: Coding environments, BI software, and analysis platforms.

• Understand AI concepts: Identify AI models, natural language processing, and robotic automation.

Data acquisition and preparation

• 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.

Data analysis

• 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.

Visualisation and Reporting

• 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.

Data Governance

• Explain data management practices: Documentation, versioning, and data lineage.

• Summarise 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.