GCP Study Hub

Understand the critical differences between tightly and loosely coupled systems, and learn how message bus architecture improves system reliability and scalability.

Understanding the distinction between using BigQuery as a data lake versus a data warehouse—and where Cloud Storage fits in—is crucial for building efficient data architectures on Google Cloud.

A comprehensive guide to implementing slowly changing dimensions in BigQuery, comparing Type 1, Type 2, and Type 3 approaches with real-world examples and decision frameworks.

A practical guide to choosing between relational and non-relational databases, covering ACID compliance, scalability, and the architectural trade-offs that matter for real systems.

A comprehensive guide to understanding all Dataflow PTransform types, from ParDo to CoGroupByKey, with practical examples for exam prep and production pipelines.

A comprehensive guide to understanding structured data in Google Cloud, covering its definition, storage options, and practical use cases for data engineers.

Understand how to safely evolve table schemas in BigQuery by comparing additive and breaking changes, with practical examples and implementation strategies.

Understanding when to use managed versus unmanaged services in Google Cloud goes beyond simple convenience. This guide explains the true trade-offs and helps you make informed decisions.

Understanding when to choose Cloud Composer over self-managed Airflow depends on honestly assessing what infrastructure complexity your team can handle.

Data Catalog tag templates provide a structured way to define custom metadata across Google Cloud services, enabling consistent data governance and fine-grained access control.