Data Engineering Fundamentals on Google Cloud

Data is the backbone of modern decision-making, but raw data is useless without the infrastructure to process, clean, and store it efficiently. Aspiring data professionals need to understand how to leverage cloud services to build reliable, scalable data systems. This text-only course guides you through the foundational concepts of data engineering on Google Cloud. You will transition from understanding basic data lifecycles to conceptualizing and structuring robust data pipelines that can handle both batch and real-time streaming data. What you'll learn: - Understand the core roles, responsibilities, and foundational terminology of modern data engineering. - Explore key Google Cloud data services including BigQuery, Cloud Storage, Pub/Sub, and Dataflow. - Design efficient batch and streaming data pipelines to ingest and process diverse datasets. - Apply modern data lakehouse concepts and ELT patterns using BigQuery and integrated tools. - Implement data governance, security, and access controls to protect sensitive cloud data assets. You will start with essential definitions of data pipelines and storage architectures before moving on to structured text-based walkthroughs of data ingestion, processing, and warehousing. This course is designed for beginners, aspiring data engineers, and IT professionals looking to transition to cloud-based data management, with no prior cloud experience required. Start reading today to build your foundation in cloud data engineering.