Learning Objectives

• Extract data from multiple sources
• Clean and manipulate data to prepare it for analysis
• Apply fundamental statistical methods to interpret data
• Understand and follow data governance and quality standards across the data life cycle
• Create effective data visualizations
• Use analytical tools to support business decision-making
• Prepare for the CompTIA Data+ certification exam (DA0-002)

Course Outline

Module 1: Data Concepts and Environments

Foundational overview of data types, data structures, and the broader data ecosystem. Examines common data formats and sources, and how data moves through an organization to support decision-making.

Module 2: Data Mining

Methods for locating and extracting relevant data from a variety of sources. Covers database querying, data collection approaches, and the tools used to gather raw data in preparation for analysis.

Module 3: Data Analysis

Use of statistical and analytical techniques to make sense of datasets. Covers descriptive statistics, trend analysis, and analytical tools that help translate data into actionable insights.

Module 4: Data Visualization

Core principles for representing data visually in a clear and meaningful way. Covers chart selection, dashboard design, data storytelling, and matching visualization types to specific datasets and audiences.

Module 5: Data Governance, Quality, and Controls

Best practices and frameworks for maintaining data accuracy, integrity, and compliance throughout the data life cycle. Covers data quality dimensions, governance policies, master data management, and the roles involved in keeping data reliable and trustworthy.