Mastering BigQuery: Building Data Warehouses for Improved Business Performance

Empower your business with smarter data and BigQuery skills

Every great decision starts with great data. To get ahead, you need the tools to bring it all together and the knowledge to use them effectively.

On this two-week course, you’ll master Google BigQuery and learn to build efficient data warehouses that turn information into insight. You’ll discover how data engineers and analysts use querying and automation to support data-driven decision making.

Build and manage your own data warehouse

Start by exploring the BigQuery platform and learning how to create a data warehouse through its interface and SQL.

You’ll see how to structure, query, and govern data effectively, transforming raw information into insights your team can put into action immediately.

Automate and transform data with Python ETL

Discover how to use Python ETL to extract, transform, and load data from multiple sources.

Through practical exercises, you’ll streamline workflows, automate repetitive tasks, and gain skills that make your data processes faster and more reliable.

Turn insights into business performance

Once your data is organised, you’ll explore advanced querying and analysis in Google BigQuery to uncover patterns and trends.

You’ll learn how to combine results, generate reports, and interpret outputs that directly inform business strategy.

By the end of the course, you’ll be able to apply your findings to support decisions, optimise processes, and identify new opportunities for your organisation.

This course is ideal for data analysts, engineers, BI professionals, and developers who want to master Google BigQuery and Python ETL. Also suited for managers and learners ready to build confidence in data-driven decision making.

This course is ideal for data analysts, engineers, BI professionals, and developers who want to master Google BigQuery and Python ETL. Also suited for managers and learners ready to build confidence in data-driven decision making.

• Understand and Navigate BigQuery: Learn the ins and outs of BigQuery's interface, set up your environment, and access datasets with ease.
• Learn the Principles of Creating Data Warehouses: Create and organize datasets, define tables, and utilize partitioning and clustering for efficient data storage.
• Perform ETL with Python: Build dynamic ETL pipelines using Python, replace and append tables, and configure schema, partitioning, and clustering.
• Comprehend Essential Query Techniques: Understand querying with SQL, exploring aggregate and window functions, and understanding data security and governance.