Transform Data into Intelligence at Cloud Scale.
Book Description
Every Great AI System Begins with a Great Data Platform
BigQuery is the backbone of modern cloud data engineering. Ultimate BigQuery for Data Engineering takes you from SQL fundamentals to building a complete production analytics platform on Google Cloud — with hands-on labs and real engineering patterns at every stage.
You begin with BigQuery internals — columnar storage, Dremel execution, and slot management — then advance through data modeling, partitioning, clustering, cost engineering, and ELT pipelines with dbt. The book covers Apache Beam, Dataflow, Cloud Composer, and streaming analytics with Pub/Sub, before addressing enterprise governance, including row-level security, column masking, data quality testing, CI/CD automation, and ML with BigQuery ML as well as Vertex AI.
The final three chapters deliver two complete capstone projects — a real-time streaming analytics system and a full warehouse ELT platform built with dbt and BigQuery — before closing with the future of BigQuery and emerging trends that will shape the next generation of cloud data engineering. Thus, by the end, you will have a portfolio of production-grade projects that prove your skills on Google Cloud!
What you will learn
• Master BigQuery internals including columnar storage, Dremel execution, and slot management.
• Design scalable data models using partitioning, clustering, and physical optimization strategies.
• Build production-grade ELT pipelines using dbt transformation layers and automated CI/CD workflows.
• Implement streaming analytics using Apache Beam, Dataflow, Pub/Sub, and Cloud Composer orchestration.
• Secure data warehouses using row-level security policies, column masking, and data quality testing.
• Deploy ML models and predictions using BigQuery ML and Vertex AI on Google Cloud.
Table of Contents
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Data Engineering Basics and BigQuery's Role
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Inside BigQuery Storage, Compute, and Execution
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Getting Data into BigQuery
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Modeling for Scale
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Partitioning, Clustering, and Optimization
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Performance and Cost Engineering
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ELT with dbt and BigQuery
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Apache Beam and Dataflow
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Spark and BigQuery Integration
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Security, Governance, and Data Quality
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BigQuery ML and Vertex AI
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Real-Time Streaming Analytics
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Enterprise Warehouse and ELT Project
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The Future of BigQuery and Emerging Trends
Index
