Curriculum

16 Chapters · 16 Lessons

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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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      Orchestration with Cloud Composer

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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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      Index

About the Course

"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!

About the Author

Dinak Lal is a data engineer specializing in cloud-native data platforms. With extensive experience building production BigQuery warehouses, dbt pipelines, and streaming analytics systems, he helps organizations transform raw data into insights. Dinak bridges the gap between SQL-focused analysts and infrastructure engineers.