Migrate Amazon Redshift Workloads to BigQuery for Faster and More Scalable Analytics
- Why get trained: Learn how to migrate Amazon Redshift schemas, SQL queries and workloads to BigQuery using BigQuery Migration Service, Data Transfer Service and Google Cloud data tools.
- Why it matters: Migrating to BigQuery helps organisations reduce infrastructure complexity, improve query performance and scale analytics more efficiently on Google Cloud.
- Who should attend: Data engineers, database engineers, data architects and Amazon Redshift users responsible for migrating data warehouse environments to BigQuery.
Move your data warehouse to Google Cloud with Trainocate Malaysia and build practical BigQuery migration skills. HRD Corp Claimable.
Overview
Become data-driven with Google Cloud. Leverage data and gain real-time insights that improve your decision-making and accelerate innovation.
In this course you will learn how to translate various concepts in Amazon Redshift to the analogous concepts in BigQuery. You will learn how the high-level architectures of Amazon Redshift and BigQuery compare, understand differences in how to configure datasets and tables, map data types in Amazon Redshift to data types in BigQuery, understand schema mapping from Amazon Redshift to BigQuery, optimize your new schemas in BigQuery, and do a high-level comparison of SQL dialects in Amazon Redshift and BigQuery.
The Google Cloud Professional Data Engineer Certification Program is a comprehensive program that provides the skills you need to advance your career and provides training to help you prepare for the industry-recognized Google Cloud Professional Data Engineer Certification exam administered by Google Cloud.
What’s in the Data Engineer learning path?
- GCPDE: Data Engineering on Google Cloud
- GCP-DWBQ: Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration
- GCP-DICDF: Data Integration with Cloud Data Fusion
- GCP-MTDBQ: Migrating Teradata Users to BigQuery
- GCP-MSFBQ: Migrating Snowflake Users to BigQuery
- GCP-MDMDP: Managing a Data Mesh with Dataplex
Advance your career in data engineering and prepare for the Google Cloud Professional Data Engineer Certification exam with this learning path.
Skills Covered
- Compare architecture and provisioning of resources in Amazon Redshift and BigQuery
- Configure datasets and tables in BigQuery
- Map and compare data types in Amazon Redshift to data types in BigQuery
- Map and optimize schemas from Amazon Redshift to BigQuery
- Translate SQL from Amazon Redshift to BigQuery
Prerequisites
- Experience using Amazon Redshift as a data warehouse for managing data and performing SQL analysis.
- Basic experience with BigQuery is recommended, but not required for this course.
Target Audience
- Anyone who are interested
Module 1: 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
Module 2: 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
Module 3: Mapping Data Types from Amazon Redshift to BigQuery
Topics:
- Mapping for data types from Amazon Redshift to BigQuery
- Data types unique to BigQuery
Objectives:
- How data types map from Amazon Redshift to BigQuery
- Understand data types unique to BigQuery
Module 4: 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
Module 5: 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
Exam & Certification
Note:Â There is no exam directly associated with this course. However, Google Cloud offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2025 and beyond. Obtaining a Google Cloud certified credential is one of the most effective ways to validate your skills and accelerate your career.
With our expert-led training, you’ll be prepared to:
- Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity, key areas driving global digital transformation.
- Prove your expertise with a globally respected credential recognized by employers worldwide.
- Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.
Explore our full range of Google Cloud certifications and start building the skills that matter today.
Training & Certification Guide
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