Google BigQuery Training

Google BigQuery Training Outline

Module 1: Interacting with BigQuery 

• Introduction to BigQuery 

• BigQuery Sandbox and Web UI 

• Command-Line Tools 

• BigQuery Classic Web UI 
   

Module 2: Running and Managing Jobs 

• Introduction 

• Running Jobs Programmatically 

• Managing Jobs 
   

Module 3: Working with Datasets 

• Define Datasets 

• Dataset Locations 

• Creating and Copying Datasets 

• Controlling Access to Datasets 

• Listing Datasets 

• Updating Dataset Properties 

• Managing Datasets 

• Availability and Durability 
   

Module 4: Working with Table Schemas 

• Specifying a Schema 

• Specifying Nested and Repeated Columns 

• Modifying Table Schemas 

• Manually Changing Table Schemas 
   

Module 5: Working with Tables 

• Managing Tables and Table Data 

• Exporting Table Data 

• Updating Table Data Using DML 
   

Module 6: Working with Partitioned Tables 

• What are Partitioned Tables? 

• Creating Ingestion-Time Partitioned Tables 

• Creating Date/Time Partitioned Tables 

• Managing and Querying Partitioned Tables 

• Using DML with Partitioned Tables 
   

Module 7: Working with Clustered Tables 

• Define Clustered Tables 

• Creating and Using Clustered Tables 
   

Module 8: Working with Views 

• Introduction to Views 

• Creating a View 

• Controlling Access to Views 

• Creating Authorised Views 

• Listing Views 

• Updating View Properties 

• Managing Views 
   

Module 9: Labelling BigQuery Resources 

• Adding Labels 

• Viewing Labels 

• Updating Labels 

• Filtering Using Labels 

• Deleting Labels 
   

Module 10: Loading Data into BigQuery 

• Loading Data from Cloud Storage 

• Loading Data from Local File 
   

Module 11: Querying BigQuery Data 

• Running Interactive and Batch Queries 

• Writing Query Results 

• Using Cached Results 

• Querying Data Using a Wildcard Table 

• Saving and Sharing Queries 

• Scheduling Queries 

• Using the Query Plan Explanation 
   

Module 12: Querying External Data Sources 

• Querying Cloud Bigtable 

• Querying Google Cloud Drive Data 
   

Module 13: Controlling BigQuery Costs 

• Estimating Storage and Query Costs 

• Custom Cost Controls 
   

Module 14: Securing BigQuery Resources 

• Encryption at Rest 

• Using Cloud DLP to Scan BigQuery Data 
   

Module 15: BigQuery API Basics 

• Authentication 

• Batch Requests 

• Paging Through Tables 

• API Performance Tips 

What You’ll Learn in this Course

This course takes you from understanding BigQuery fundamentals to executing advanced data analytics and optimisation techniques. Each stage builds confidence in managing and querying cloud-based data. 
 

• Learn the fundamentals of BigQuery architecture and key features 

• Learn how to create, manage, and query large datasets effectively 

• Learn to design data models for analytics and reporting 

• Learn how to optimise query performance and manage costs 

• Learn to integrate BigQuery with Google Data Studio and ML tools 

• Learn how to apply data analytics for business insights and automation