Data Architecture Fundamentals for Analytics and Reporting

Modern organizations rely on clean, accessible data to drive informed business decisions, but unstructured or fragmented systems often create bottlenecks. This text-based course guides you through core data architecture principles, helping you understand how data moves from operational sources into robust analytics environments. You will explore foundational concepts, storage paradigms, and modeling techniques to support fast, reliable reporting across an enterprise. What you'll learn: - Understand core data architecture terminology, lifecycle stages, and governance fundamentals - Design effective analytical data models using dimensional modeling, star schemas, and snowflake schemas - Compare relational warehouses, data lakes, and modern lakehouse design patterns - Plan scalable integration pipelines using current ETL and ELT batch and streaming approaches - Apply data quality checks, cataloging standards, and access control strategies - Evaluate modern architectural paradigms such as modular data stacks and decentralized data mesh concepts The course begins with foundational vocabulary and architectural building blocks before walking step-by-step through storage design, pipeline patterns, and practical reporting considerations. It is designed for beginners, data analysts, and aspiring engineers with no prior architecture experience required. Start reading today to build a strong foundation in modern data architecture.