Course Overview of Data Warehousing with BigQuery

This course provides learners with an in-depth understanding of BigQuery internals and advanced data warehousing concepts on Google Cloud. Through instructor-led sessions, demonstrations, and hands-on labs, participants will learn how to design optimized schemas, improve query performance, manage workloads, implement security best practices, automate workloads, and build machine learning models using BigQuery ML.

After completing this Data Warehousing with BigQuery, participants will be able to:

  • Describe BigQuery architecture fundamentals and query processing internals.
  • Design optimized storage schemas using partitioning, clustering, and nested structures.
  • Implement batch and streaming ingestion pipelines.
  • Optimize queries and improve read performance.
  • Manage workloads, monitor usage, and control BigQuery costs.
  • Secure BigQuery environments using IAM, encryption, and governance controls.
  • Build and deploy machine learning models using BigQuery ML.

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Key Features of Data Warehousing with BigQuery

  • Advanced BigQuery Architecture Learning

  •  Storage and Schema Optimization 

  •  Hands-On Data Ingestion and Transformation Labs 

  • Query Optimization and Read Performance 

  • Workload Management and Cost Optimization 

  • Monitoring, Logging, and Governance 

  • Security and Data Protection 

  • Automation and BigQuery ML 

Who should Attend Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration?

  • Data Engineers
  • Data Analysts
  • Data Scientists
  • Cloud Developers
  • BigQuery Administrators

Why choose CloudThat as your training partner for Data Warehousing with BigQuery?

  •  Specialized GCP AI and AgentOps Expertise - CloudThat specializes in cloud, Generative AI, and agentic application technologies and delivers focused Google Cloud training programs with enterprise operational use cases.
  • Industry-Recognized Trainers - Our trainers are certified Google Cloud professionals with expertise in Vertex AI, AI agents, DevOps, MLOps, observability, and AI governance workflows.
  • Hands-On Learning Approach - CloudThat emphasizes practical learning through guided labs, CI/CD exercises, debugging workflows, evaluation systems, and AI security implementation scenarios.
  • Customized Learning Paths - Training programs are designed for developers, DevOps engineers, ML engineers, and cloud professionals working with AI agent systems. 
  • Interactive Learning Experience - Sessions include demonstrations, collaborative operational workflows, troubleshooting activities, quizzes, and interactive discussions.
  • Placement Assistance and Career Support - CloudThat supports learners with AI learning paths, interview preparation, operational best practices, and career guidance in Generative AI and AgentOps. 
  • Continuous Learning and Updates - Course content is continuously updated to align with the latest advancements in Vertex AI, AI operations, observability, security, and AI FinOps practices.
  • Positive Reviews and Testimonials - Thousands of professionals and enterprises trust CloudThat for advanced cloud, AI, MLOps, and Google Cloud training programs.    

Course Outline for Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration Download Course Outline

  • BigQuery Core Infrastructure
  • BigQuery Storage
  • Query Processing
  • Data Shuffling

  • Partitioning and Clustering
  • Nested and Repeated Fields
  • ARRAY and STRUCT
  • Schema Design Best Practices

  • Batch Ingestion
  • Streaming Ingestion
  • Storage Write API
  • Data Transfer Service
  • External Data Sources

  • Slowly Changing Dimensions
  • DML Statements
  • DML Best Practices

  • Cache Optimization
  • Materialized Views
  • BI Engine
  • Storage Read API

  • Query Execution
  • Aggregation
  • JOIN Optimization
  • Filtering and Ordering
  • Function Best Practices

  • BigQuery Slots
  • Pricing Models
  • Slot Reservations
  • Cost Optimization

  • Cloud Monitoring
  • BigQuery Admin Panel
  • Cloud Audit Logs
  • INFORMATION_SCHEMA

  • IAM Policies
  • Authorized Views
  • Encryption
  • Data Governance
  • Data Catalog and DLP API

  • Scheduling Queries
  • Scripting
  • Stored Procedures
  • Integration with Big Data Products

  • BigQuery ML Introduction
  • Prediction Models
  • Recommendation Systems
  • Demand Forecasting
  • Time-Series Models
  • Explainability

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Course ID: 28733

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FAQs for Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration

This course is designed for data engineers, analysts, developers, and administrators working with BigQuery at scale.

Yes. The course includes multiple labs, demos, and optimization exercises.

BigQuery, BigQuery ML, Cloud Monitoring, Data Catalog, DLP API, and related Google Cloud services.

Yes. A major focus of the course is query optimization, workload management, and performance tuning.

Yes. Learners will build and deploy machine learning models using BigQuery ML.

3-day instructor-led training with lectures, labs, demos, and hands-on activities.

Yes. Basic BigQuery and SQL knowledge are expected prerequisites.

Yes. A course completion certificate will be provided after successful participation.

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