Adding CompTIA Data+ to my certification to acquire.
Data+ (V2) exam objectives summary
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.
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.
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.
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
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.
