Cloud Data Engineering Fundamentals with BigQuery and Dataflow

As organizations generate massive volumes of data daily, the demand for structured, reliable data pipelines has never been higher. Understanding how to ingest, transform, and store this data efficiently on modern cloud infrastructure is a foundational skill for any aspiring data professional. This text-based course guides you from absolute beginner to confidently understanding cloud data architecture. You will learn how to design data pipelines, manage scalable storage, and process data streams using industry-standard cloud tools. What you'll learn: - Understand core data engineering roles, responsibilities, and fundamental pipeline architectures. - Explore cloud storage options and select the right database or data lake solution for your analytical needs. - Query and analyze large datasets using BigQuery and modern SQL optimization techniques. - Build batch and streaming pipelines using Dataflow and pub-sub messaging patterns. - Apply modern data lakehouse concepts and basic pipeline orchestration to ensure data quality. You will start with fundamental data engineering terminology and architecture concepts before reading through step-by-step pipeline design workflows. The material covers data ingestion, transformation, and storage, complete with conceptual exercises to test your understanding. This course is designed for absolute beginners, aspiring data engineers, and analysts looking to transition to cloud technologies. No prior cloud experience or programming background is required to get started. Start building your foundation in cloud data engineering today.