BigQuery Fundamentals for Snowflake Pros
Master BigQuery essentials. Learn architecture, resource management, data ingestion, and query optimization. Compare with Snowflake for seamless transition.
Master BigQuery essentials. Learn architecture, resource management, data ingestion, and query optimization. Compare with Snowflake for seamless transition.
This course is designed for Snowflake professionals transitioning to BigQuery. It covers BigQuery's architecture, resource provisioning, data definition model, and Google Cloud IAM. Students learn to create and secure data assets, implement best practices for schema design, data ingestion, and query optimization. The course emphasizes comparisons between Snowflake and BigQuery, helping professionals leverage their existing knowledge while adapting to BigQuery's unique features and capabilities.
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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 Snowflake and BigQuery
Optimize query performance and control costs in BigQuery
Apply Google Cloud IAM model to secure BigQuery resources
Skills you'll gain
This course includes:
4 Minutes PreRecorded video
6 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This course introduces BigQuery fundamentals to professionals familiar with Snowflake. It covers six key areas: BigQuery architecture and resource provisioning, data definition model, Google Cloud IAM, data ingestion, schema design and optimization, and SQL in BigQuery. Each module provides a comprehensive overview of BigQuery features and best practices, while drawing comparisons to Snowflake to facilitate understanding. The course combines theoretical knowledge with hands-on labs, allowing students to apply concepts in a practical setting. By the end, participants will be equipped to effectively work with BigQuery, understanding its similarities and differences compared to Snowflake.
BigQuery Architecture and Resource Provisioning
Module 1 · 1 Hours to complete
BigQuery Data Definition Model
Module 2 · 16 Minutes to complete
BigQuery and Google Cloud IAM
Module 3 · 1 Hours to complete
BigQuery Data Ingestion
Module 4 · 16 Minutes to complete
BigQuery Schema Design and Optimization
Module 5 · 1 Hours to complete
SQL in BigQuery
Module 6 · 1 Hours to complete
Fee Structure
Instructor
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Frequently asked questions
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