Build Data Warehouse using BigQuery
Design cloud data warehouses and ETL workflows with BigQuery
Explore how to design and manage cloud data warehouses using Google BigQuery. Learn to organize datasets, automate ETL workflows, and write efficient analytical queries for large-scale data projects. Build practical skills for real-world data engineering and analytics tasks.
Starweaver | Jun 2026 | 109 min
What You Will Learn
You will start by getting comfortable with the BigQuery platform and its interface. Step by step, you will create datasets and tables using both the UI and code. Through hands-on exercises, you will build ETL workflows, apply data partitioning and clustering, and practice writing complex SQL queries. By the end, you will have a working knowledge of data governance and automation.
Key Features
- Set up BigQuery environments and organize datasets for scalable data storage
- Build automated ETL workflows using SQL, Python, and Jupyter Notebook
- Write advanced queries with aggregate, window functions, and user-defined logic
Target Audience
This course is designed for data analysts, engineers, and business intelligence professionals who want hands-on experience with BigQuery. If you have a basic understanding of SQL and core data concepts, you will benefit most. It is also a great fit for aspiring analysts looking to build practical cloud data management skills.
