BigQuery Migration and Fundamentals for Teradata Professionals

Transitioning from a traditional on-premises data warehouse to a modern cloud-native solution requires a shift in how you think about storage, compute, and query execution. This text-based course is designed specifically to help Teradata professionals map their existing database knowledge directly to BigQuery. You will learn how to translate familiar Teradata concepts—such as primary indexes, databases, and BTEQ scripts—into BigQuery datasets, partitioned tables, and modern SQL workflows. By understanding the core architectural differences, you will be able to optimize queries for both cost and performance in a serverless environment. What you'll learn: - Compare Teradata architecture directly with BigQuery's separation of storage and compute - Translate Teradata SQL patterns and functions into standard GoogleSQL equivalents - Configure table partitioning and clustering to optimize query performance and control costs - Manage data loading, schema design, and nested or repeated fields in a cloud environment - Understand modern data operations, including basic integration with version-controlled analytics pipelines The course begins with foundational concepts, comparing traditional architecture with modern serverless data warehousing. You will then progress through practical written scenarios, exploring schema design, SQL translation, and performance optimization techniques. This course is designed for data warehouse administrators, developers, and analysts who are familiar with Teradata and want to transition to BigQuery. No prior cloud experience is required. Start reading today to confidently migrate your data warehousing expertise to the cloud.