Data Preparation and Processing with Azure Databricks

In today's data-driven world, processing massive datasets efficiently is a critical skill for modern data professionals. Azure Databricks provides a unified, collaborative platform that simplifies big data engineering and analytics at scale. This text-based course guides you through the foundational concepts of data preparation and processing. You will understand how to build reliable data pipelines, implement modern lakehouse architectures, and manage data governance effectively. What you'll learn: 1. Understand the core architecture of Azure Databricks and Delta Lake. 2. Ingest raw data from multiple sources into a centralized lakehouse. 3. Clean, transform, and structure data using PySpark and SQL. 4. Implement data governance and security rules with Unity Catalog. 5. Apply data quality checks and schema enforcement to ensure reliable pipelines. 6. Build and optimize scalable data pipelines for downstream analytics. You will start with fundamental cloud data concepts and step-by-step terminology before moving into practical pipeline design. The course utilizes written explanations, clear code examples, and conceptual walkthroughs to build your confidence. Designed specifically for beginners, this course requires no prior experience with cloud data platforms. Start your journey toward mastering modern cloud data engineering today.