Big Data Engineering Foundations: Pipeline Design and Storage

Modern organizations generate vast amounts of information that require specialized architectures to store, process, and analyze efficiently. This course introduces you to the core principles of big data systems, giving you the skills needed to understand scalable data infrastructure and pipeline mechanics. You will progress from foundational terminology to practical workflow design, preparing you to tackle real-world data challenges. In this course, you will learn to: - Understand key big data concepts, architectural patterns, and storage definitions - Explore distributed storage systems and computing paradigms like batch and stream processing - Analyze processing tools such as Hadoop and Spark for managing massive datasets - Learn modern data storage patterns, including data lakehouse architectures and columnar file formats - Design robust data ingestion and transformation pipelines using clean code logic - Apply your knowledge by completing a portfolio-ready data pipeline design exercise The course starts with essential terminology and fundamental infrastructure concepts before moving into practical pipeline construction and query optimization. You will read structured explanations and analyze clear code snippets to understand each component thoroughly. This text-based program is designed for beginners and aspiring tech professionals looking to enter the field with no prior big data experience required. Start reading today and build your foundation in big data development.