This course, offered by Google Cloud, is designed for professionals familiar with SQL-based cloud data warehouses in Teradata who are looking to make the transition to BigQuery. Through interactive lectures and hands-on labs, you will learn the fundamentals of BigQuery, including resource provisioning, data asset creation, data ingestion, and query optimization. The course also covers the similarities and differences between Teradata and BigQuery, providing valuable insights for professionals looking to work in BigQuery.
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Gain comprehensive knowledge of BigQuery through modules covering architecture, resource provisioning, data definition, IAM, data ingestion, schema design, optimization, and SQL implementation.
The BigQuery Architecture and Resource Provisioning module provides insights into the architecture and resource provisioning of BigQuery. Through lectures, labs, and quizzes, you will understand how to monitor workloads effectively.
The BigQuery Data Definition Model module covers important aspects related to data definition in BigQuery. This module provides essential knowledge for professionals working with data assets in BigQuery.
The BigQuery and Google Cloud IAM module focuses on the security aspects of BigQuery and IAM integration. This module equips professionals with the skills to secure and manage access to data assets.
The BigQuery Data Ingestion module offers insights into best practices for ingesting data into BigQuery. Professionals will learn about efficient data ingestion techniques and tools available in BigQuery.
The BigQuery Schema Design and Optimization module provides comprehensive knowledge of schema design and optimization techniques in BigQuery. This module equips professionals with the skills to design efficient schemas and optimize query performance.
The SQL in BigQuery module covers the implementation of SQL in BigQuery. This module provides hands-on experience in writing and executing SQL queries in BigQuery, essential for leveraging the power of BigQuery for data analysis.
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