This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Redshift and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Redshift, you also learn about similarities and differences between Redshift and BigQuery to help you get started with data warehouses in BigQuery.
BigQuery Fundamentals for Redshift Professionals
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Describe BigQuery’s architecture, resource provisioning, and data definition model.
Create, secure, and share BigQuery data assets using best practices.
Implement common patterns and best practices for designing schemas, ingesting data, and querying data in BigQuery.
Compare and contrast the differences and commonalities between Redshift and BigQuery.
Details to know
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Assessments
6 assignments
Taught in English
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There are 6 modules in this course
This introductory module summarizes the key details of BigQuery architecture and resource provisioning including how BigQuery utilizes slots to execute SQL queries and workload management in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences between Redshift and BigQuery architecture and resource provisioning to help you get started with BigQuery.
What's included
1 video1 reading1 assignment1 app item
This module summarizes the key details of BigQuery’s resource hierarchy and data definition model, including how to create datasets and tables in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences between the Redshift and BigQuery resource hierarchies and primary data types to help you start working with data in BigQuery.
What's included
1 reading1 assignment
This module summarizes the key details of the Google Cloud Identity and Access Management (IAM) model, including how roles and permissions are applied to datasets and tables in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in roles and permissions between Redshift and BigQuery to help you start securing and sharing your data in BigQuery.
What's included
1 reading1 assignment1 app item
This module summarizes the primary options and best practices for ingesting data into BigQuery, including batch data loading, streaming ingestion, and queries to external data sources. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in data ingestion options between Redshift and BigQuery to help you start reading and loading your data into BigQuery.
What's included
1 reading1 assignment
This module summarizes common patterns and best practices for designing and optimizing table schemas in BigQuery, including the use of nested and repeated fields, partitioning, and clustering. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in schema usage and design between Redshift and BigQuery to help you start structuring and optimizing your data in BigQuery.
What's included
1 reading1 assignment1 app item
This module summarizes the key features and operations of the Google Standard SQL dialect used in BigQuery and best practices for optimizing query performance and controlling costs in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in the SQL dialects and features between Redshift and BigQuery to help you start running and optimizing queries in BigQuery.
What's included
1 reading1 assignment1 app item
Instructor
Offered by
Recommended if you're interested in Cloud Computing
Google Cloud
Illinois Tech
University of California, Davis
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.