Overview

GCP: Database and Storage is the second course of Exam Prep: Google Certified Professional Cloud Architect Specialization. This course offers a comprehensive journey through advanced data, storage, analytics, and reliability services on Google Cloud Platform (GCP) using Cloud SQL, Bigtable, Firestore, Spanner, and BigQuery, providing architectural understanding, real-world analytics use cases, and capacity planning strategies. Learners will explore Cloud Storage, Storage Transfer Service, and Transfer Appliance, focusing on cost optimization and integrations with other cloud services. The course also introduces GCP-native data pipelines using Cloud Dataflow, Cloud Dataproc, and Cloud Dataprep, empowering learners to process and transform data at scale. This course is ideal for: - Cloud engineers and DevOps professionals moving into architecture roles. - System administrators and solution architects aiming to validate their GCP skills. - IT professionals seeking to grow into high-impact cloud design and governance roles. - Anyone who wants to master how to design scalable, secure, and resilient solutions on Google Cloud. By the end of the course, you will be able to: - Understand Google Cloud’s Core Managed Databases and Storage Options. - Develop Proficiency in Data Analytics and Visualization Tools. - Implement Scalable Data Processing and Transfer Pipelines.

Syllabus

Databases in Google Cloud

Welcome to Week 1. This week, we’ll begin by exploring Cloud SQL, its supported database engines (MySQL, PostgreSQL, and SQL Server), and how it simplifies traditional relational database management in the cloud. You’ll also get familiar with Cloud Spanner as well as Cloud Bigtable. Next, we’ll explore BigQuery and its key features, Google’s powerful serverless data warehouse. You’ll learn how to manage and monitor your data analytics pipelines, build dashboards with Looker Studio. We’ll then shift focus to NoSQL databases like Firestore, and cover best practices for database capacity planning and performance optimization. You’ll also explore Cloud Dataflow, Cloud Dataproc, and Cloud DataPrep—essential tools for data processing, ETL pipelines, and workflow orchestration. Finally, we’ll introduce some of Google’s AI-powered APIs including Cloud Speech-to-Text, Vision API, and Translate API. By the end of this module, you’ll have a well-rounded understanding of Google Cloud’s database and analytics ecosystem, and how to architect data-driven applications that are scalable, cost-effective, and intelligent.

Storage in Google Cloud

Welcome to Week 2. This week, we’ll explore Google Cloud’s storage solutions and services, starting with an overview of the different storage options available on GCP, including object, block, and file storage. Through hands-on demonstrations, we’ll walk through setting up Cloud Storage buckets, uploading objects, and managing access policies. You'll also be introduced to Storage Transfer Service, which enables you to efficiently migrate data from on-premises or other cloud providers to Google Cloud. We’ll discuss Transfer Appliance, a secure, high-capacity hardware solution designed for large-scale data transfers when network limitations exist. By the end of this module, you’ll have practical experience with storage provisioning and migration, and you’ll be equipped to choose the right GCP storage solution for your use case while ensuring reliable and cost-effective data transfer strategies.