The CompTIA Data+ certification is designed for professionals seeking to enhance their data analytics skills, focusing on transforming business requirements into data-driven decisions. The course content is structured into five key domains, each contributing to the comprehensive skill set required for effective data analysis:

Data Concepts and Environments (15%):

• Understanding relational and non-relational databases, including the use of tables, primary keys, and normalization.
• Describing types of data processing and storage systems and explaining how data evolves over time.
• Identifying various data types, structures, formats, and markup languages.

Data Mining (25%):

• Explaining data integration and collection methods, such as ETL (Extract, Transform, Load) processes and API/web scraping techniques.
• Identifying common reasons for data cleansing and profiling, including addressing redundant, duplicated, missing, or invalid data.
• Executing data manipulation techniques like filtering, sorting, transposing, and appending data.

Data Analysis (23%):

• Applying descriptive statistical methods, including measures of central tendency, dispersion, and frequency distributions.
• Describing key analysis techniques, such as trend and performance analysis.
• Understanding the use of different statistical methods, including hypothesis testing and correlation analysis.

Visualization (23%):

• Using appropriate types of visualizations, including basic and advanced visuals, to effectively communicate data insights.
• Expressing business requirements in report formats, considering audience needs and data source considerations.
• Designing components for reports and dashboards, utilizing standard elements and creating narratives.

Data Governance, Quality, and Controls (14%):

• Summarizing the importance of data governance, including access and security requirements.
• Applying quality control to data, describing characteristics, rules, and metrics of data quality.
• Explaining master data management concepts and processes.