Training Google Cloud

Training goals

code: G-MTUBQ | version: v1.0

In this course you will learn how to translate various concepts in Teradata to the analogous concepts in BigQuery. You will learn how the high-level architectures of Teradata and BigQuery compare, understand differences in how to configure datasets and tables, map data types in Teradata to data types in BigQuery, understand schema mapping from Teradata to BigQuery, optimize your new schemas in BigQuery, and do a high-level comparison of SQL dialects in Teradata and BigQuery.

 

What you'll learn

  • Compare architecture and provisioning of resources in Teradata and BigQuery
  • Configure datasets and tables in BigQuery
  • Map and compare data types in Teradata to data types in BigQuery
  • Map and optimize schemas from Teradata to BigQuery
  • Translate SQL from Teradata to BigQuery

 

Audience

This course is intended for data engineers and analysts familiar with Teradata who want to migrate workloads to Google BigQuery.

 

Products

  • BigQuery

Conspect Show list

  • Understanding BigQuery Architecture
    • Topics
      • Quick reminder of Amazon Redshift architecture
      • Overview of BigQuery architecture
      • Separation of compute and storage in BigQuery
      • BigQuery Slots
      • Workload management in BigQuery
    • Objectives
      • Compare architecture and provisioning of resources in Amazon Redshift and BigQuery
      • Describe the concept of a slot in BigQuery
  • Creating Datasets and Tables in BigQuery
    • Topics
      • Resource Hierarchy in Amazon Redshift
      • Resource Hierarchy in BigQuery
      • Creating resources in BigQuery
      • Sharing resources in BigQuery
    • Objectives
      • Understand the resource hierarchy in BigQuery
      • Configure datasets and tables in BigQuery
    • Activities
      • Lab: Provisioning and Managing Resources in BigQuery
  • Mapping Data Types from Teradata to BigQuery
    • Topics
      • Mapping for data types from Teradata to BigQuery
      • Data types unique to BigQuery
    • Objectives
      • How data types map from Teradata to BigQuery
      • Understand data types unique to BigQuery
  • Schema Optimization and Mapping
    • Topics
      • Schema definitions in BigQuery
      • Partitioning in BigQuery
      • Clustering in BigQuery
    • Objectives
      • Define schemas in BigQuery
      • Implement partitioning and clustering in BigQuery
    • Activities
      • Lab: Schema Migration to BigQuery
  • SQL Translation from Amazon Redshift to BigQuery
    • Topics
      • SELECT statements
      • DML statements
      • DDL statements
      • UDFs and Procedures
    • Objectives
      • Understand query capabilities in BigQuery SQL
      • Write user-defined functions and procedures in BigQuery SQL
    • Activities
      • Lab: Writing SQL for BigQuery
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Additional information

Prerequisites

Experience using Teradata as a data warehouse for managing data and performing SQL analysis. Basic experience with BigQuery is recommended, but not required for this course.
Difficulty level
Duration 1 day
Certificate

The participants will obtain certificates signed by Google Cloud (course completion).
Trainer

Authorized Google Cloud Trainer.

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