Introduction:
As organizations increasingly rely on data to inform strategic business decisions, demand is rising for professionals who can translate raw information into actionable insights. The CompTIA Data+ certification is an early-career data analytics certification that validates the skills required to collect, analyze, interpret, and present data with clarity and confidence.
This 5-day certification training course prepares you for the CompTIA Data+ certification exam (DA0-001). It’s ideal for aspiring data analysts, business professionals, or IT specialists looking to deepen their understanding of data analysis and data governance. You’ll gain hands-on data analytics experience across the entire data life cycle, from data mining and transformation to data visualization and reporting.
Whether you’re new to the field or want to formalize your data analytics knowledge, this course gives you the foundation to work with complex datasets while adhering to governance and quality standards throughout the entire process.
Objectives:
This course teaches foundational data analytics skills aligned with the CompTIA Data+ certification exam (DA0-001). You’ll learn how to mine data from multiple sources, clean and manipulate it for analysis, and apply basic statistical methods to interpret data effectively. The course also emphasizes data governance and quality standards throughout the entire data life cycle. By the end of the training, you’ll be able to build compelling visualizations, use analytical tools to support business decisions, and confidently pursue this early-career data analytics certification.
Course Outline:
1 – Identifying Basic Concepts of Data Schemas
- Relational vs. non-relational databases
- Tables, primary keys, normalization
2 – Understanding Different Data Systems
- Types of data processing and storage
- How data changes over time
3 – Understanding Types and Characteristics of Data
- Structured vs. unstructured data
- File types and field data
4 – Comparing Data Structures, Formats, and Languages
- CSV, JSON, XML
- Common code languages used for data
5 – Data Integration and Collection
- ETL processes
- API/web scraping
- Public and survey data collection
6 – Data Cleansing and Profiling
- Handling missing or invalid data
- Converting and validating data
7 – Data Manipulation Techniques
- Querying, appending, and transforming data
- Creating calculated fields and variables
8 – Data Optimization
- Query optimization
- Efficient function use
9 – Descriptive Statistics
- Central tendency and dispersion
- Frequency and percentages
10 – Key Analytical Techniques
- Introduction to common analysis types
11 – Statistical Methods
- Hypothesis testing
- Relationships between variables
12 – Data Visualization
- Basic and advanced visuals
- Geographical data maps
- Telling stories with visuals
13 – Business Reporting Requirements
- Identifying audience needs
- Data source considerations
- Sorting and filtering
14 – Designing Reports and Dashboards
- Narrative and design elements
- Deployment considerations
15 – Deployment Considerations
- Timing, updating, and types of reports
16 – Data Governance
- Access policies
- Security and entity relationship rules
17 – Data Quality Control
- Data validation and quality metrics
18 – Master Data Management
- MDM basics and processes
Enroll in this course
$2,475.00 – $2,495.00