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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps.
We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views.
After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
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Overview
Syllabus
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- Introduction
- Overview of what you will learn in this course
- Advanced Functions and Clauses
- Deepen your knowledge of SQL on BigQuery by learning about more advanced functions like statistical approximations, analytical window queries, user-defined functions, and WITH clauses.
- Schema Design and Nested Data Structures
- Walkthrough the evolution of how traditional databases handle dataset scale and compare how BigQuery was developed to address scaling limitations. Deep dive into nested and repeated fields which are a key part of denormalized BigQuery data structures.
- Optimizing for Performance
- Learn the fundamental pieces of work that impact BigQuery performance and how to optimize your queries for speed.
- Advanced Insights with Vertex AI Workbench
- Introducing Vertex AI Workbench -- a key tool in the Data Scientist toolkit -- which enables analysts to collaborate through the use of scalable cloud notebooks.
- Data Access
- Securing and sharing your BigQuery datasets is critical for any organization. Learn what Google Cloud and BigQuery tools are available to you to permission control and share your data.
- Summary
- Summary of the course ley learning points
