Instructor: Google Cloud Training

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 Teradata and BigQuery.

    • Skills you'll gain

    There are 6 modules in this course

    This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Teradata 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 Teradata, you also learn about similarities and differences between Teradata and BigQuery to help you get started with data warehouses in BigQuery.

    BigQuery Data Definition Model

    BigQuery and Google Cloud IAM

    BigQuery Data Ingestion

    BigQuery Schema Design and Optimization

    SQL in BigQuery

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