Master Google BigQuery with lot of examples and real-world case studies
Unlock the power of Google BigQuery in this comprehensive course designed for beginners and data professionals alike. Whether you’re new to cloud data warehousing or want to master advanced techniques, this course guides you through every critical aspect of BigQuery — from the fundamentals to real-world case studies.
What you’ll learn
- Understand the fundamentals of Google BigQuery, including architecture, storage, and pricing.
- Load and manage data efficiently using various methods such as Cloud Storage, SDK, Console and streaming inserts..
- Apply advanced concepts like partitioning, clustering, and working with arrays.
- Implement a complete end-to-end case study to simulate a real-world data analytics pipeline using BigQuery..
Course Content
- Notes and Datasets –> 2 lectures • 1min.
- Lets get into to BigQuery –> 8 lectures • 7hr 41min.
Requirements
Unlock the power of Google BigQuery in this comprehensive course designed for beginners and data professionals alike. Whether you’re new to cloud data warehousing or want to master advanced techniques, this course guides you through every critical aspect of BigQuery — from the fundamentals to real-world case studies.
We begin by introducing BigQuery and its key features, followed by hands-on sessions where you’ll learn how to create tables using different methods, work with external vs native tables, and optimize your storage using partitioning and clustering.
You’ll also gain deep practical experience working with complex data types like JSON and ARRAY, building logical, materialized, and authorized views, and exploring how BigQuery handles various data processing scenarios.
To reinforce your learning, we’ll walk through real-world case studies, including a Spotify analytics project and a Social Media case study assignment, so you can confidently apply your knowledge in real data scenarios.
What you’ll cover in this section:
- Introduction to BigQuery and how it fits into Google Cloud
- Methods for creating and managing tables (Native vs External)
- Storage optimization techniques: Partitioning & Clustering
- Handling nested and repeated fields like JSON and ARRAY
- Creating and using views: logical, materialized, and authorized
- Spotify case study: building insights from real songs data
- Hands-on assignment: analyze and report on social media engagement
By the end of this section, you’ll not only understand the theory but will also have hands-on experience building real data pipelines and analytics projects using BigQuery.