ETL Data Integration Fundamentals

Every data-driven decision starts with high-quality, accessible data, yet most information begins in a raw and disconnected state. This course guides you through the essential ETL (Extract, Transform, Load) process, teaching you how to bridge the gap between raw data sources and actionable insights. You will learn to build reliable data pipelines by mastering the mechanics of data movement and preparation. By understanding how to handle different data formats and structures, you will gain the skills necessary to ensure data integrity across your organization. What you'll learn: - Extract data from various formats including CSV, JSON, and relational databases - Transform raw information through cleaning, filtering, and data type standardization - Implement data validation techniques to ensure accuracy and consistency - Understand the difference between traditional ETL and modern ELT cloud workflows - Load processed data into centralized repositories like data warehouses or lakes - Apply basic automation principles to keep data pipelines running smoothly The course begins with foundational terminology and the data lifecycle before moving into practical written exercises that simulate real-world data movement scenarios. You will explore how to handle common data quality issues and how to structure data for optimal querying. This course is designed for beginners and business professionals looking to understand the technical mechanics of data movement without prior engineering experience. No specific software prerequisites are required to start. Begin your journey into the world of data engineering today.