CompTIA Data+ (CTIA_DATA)

As organizations increasingly rely on data to guide business decisions, professionals who can translate raw information into actionable insights are in high demand. CompTIA Data+ is an early-career data analytics certification validating skills to collect, analyze, interpret, and present data with clarity and confidence.

This 5-day course prepares you for the CompTIA Data+ certification exam (DA0-002). You will work across the data life cycle, including data mining and transformation, statistical methods, data visualization, business reporting, and data governance and quality.

1. Identifying Basic Concepts of Data Schemas
   1. Relational vs. non-relational databases
   2. Tables, primary keys, normalization
2. Understanding Different Data Systems
   1. Types of data processing and storage
   2. How data changes over time
3. Understanding Types and Characteristics of Data
   1. Structured vs. unstructured data
   2. File types and field data
4. Comparing Data Structures, Formats, and Languages
   1. CSV, JSON, XML
   2. Common code languages used for data
5. Data Integration and Collection
   1. ETL processes
   2. API/web scraping
   3. Public and survey data collection
6. Data Cleansing and Profiling
   1. Handling missing or invalid data
   2. Converting and validating data
7. Data Manipulation Techniques
   1. Querying, appending, and transforming data
   2. Creating calculated fields and variables
8. Data Optimization
   1. Query optimization
   2. Efficient function use
9. Descriptive Statistics
   1. Central tendency and dispersion
   2. Frequency and percentages
10. Key Analytical Techniques
    1. Introduction to common analysis types
11. Statistical Methods
    1. Hypothesis testing
    2. Relationships between variables
12. Data Visualization
    1. Basic and advanced visuals
    2. Geographical data maps
    3. Telling stories with visuals
13. Business Reporting Requirements
    1. Identifying audience needs
    2. Data source considerations
    3. Sorting and filtering
14. Designing Reports and Dashboards
    1. Narrative and design elements
    2. Deployment considerations
15. Deployment Considerations
    1. Timing, updating, and types of reports
16. Data Governance
    1. Access policies
    2. Security and entity relationship rules
17. Data Quality Control
    1. Data validation and quality metrics
18. Master Data Management
    1. MDM basics and processes

Each student receives a comprehensive set of materials, including course notes and all class examples.

Experience in the following would be useful for this Data class: