This course provides a practical, hands-on introduction to Google BigQuery for building scalable data warehouses using BigQuery and performing advanced cloud-based analytics. Learners will explore what is a data warehouse, how modern enterprise data warehouse systems operate, and how to efficiently manage large datasets using Google BigQuery. Through real-world exercises and guided demonstrations, participants will learn how to set up and access BigQuery, build a data warehouse with BigQuery using both the web interface and Python, and apply optimization techniques to improve query performance, scalability, and cost efficiency in cloud environments. Designed for data analysts, data engineers, and business intelligence professionals, this Data warehouse using BigQuery course is also valuable for aspiring analysts seeking to strengthen SQL expertise and gain practical experience with modern data warehouse architectures and enterprise-scale data management. Learners will develop hands-on skills in querying, transforming, and analyzing large datasets to support data-driven decision-making and business intelligence initiatives. A basic understanding of SQL and foundational data concepts is recommended. By the end of the course, participants will be able to design scalable data warehouse with BigQuery solutions, execute complex analytical queries, and extract actionable insights using the full capabilities of Google BigQuery.
What you'll learn
set up and access Google BigQuery
build a data warehouse using the web interface and Python
apply optimization techniques for query performance and scalability
query, transform, and analyze large datasets
Course objectives
understand data warehouse concepts
efficiently manage large datasets in cloud environments