Exam Prep: Google Cloud Professional Cloud Database Engineer

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This specialization is designed to help you build practical, real-world skills in designing, deploying, and managing databases using Google Cloud. Across five comprehensive courses, you’ll explore a wide range of database services including Cloud SQL, Cloud Spanner, AlloyDB, Bigtable, and Firestore, covering both relational and NoSQL use cases used in modern applications. You’ll learn how to choose the right database service based on application requirements, design scalable and highly available architectures, and implement best practices for performance optimization, cost management, and reliability. The specialization also focuses on essential operational skills such as database migration, monitoring, troubleshooting, security, and automation. Through hands-on demonstrations and real-world scenarios, you’ll gain experience working with production-like environments and understand how different database services fit into cloud-native architectures. The content is also aligned with the Google Cloud Certified Professional Cloud Database Engineer certification, helping you strengthen the core concepts and practical skills needed to approach the exam with confidence. By the end of this program, you’ll be able to design and manage production-ready database solutions on Google Cloud and be well-prepared for both real-world roles and certification success.

Syllabus

Course 1: Google Cloud SQL: Design, Deploy & Optimize Databases
Course 2: Google Cloud Spanner: Design, Scale & Operate Databases
Course 3: Google Cloud AlloyDB: Design & Operate Databases
Course 4: Google Cloud Bigtable: Designing and Operating Databases
Course 5: Google Cloud Firestore: Designing and Managing Databases

Courses

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Build practical skills to design, manage, and scale modern NoSQL databases using Google Cloud Firestore. This course introduces Firestore fundamentals, including its serverless architecture and support for real-time, scalable applications. You will learn how to analyze database capacity and usage patterns, design highly available and resilient database solutions, and implement connectivity and access management strategies. The course also covers monitoring, troubleshooting, and backup and recovery techniques to ensure operational reliability. You’ll explore how to optimize database cost and performance, automate routine tasks, and design data migration strategies. Through hands-on demonstrations, you will evaluate Native mode vs Datastore mode, configure security policies, and perform backup and restore operations. By the end of this course, you will be able to design, deploy, and manage production-ready Firestore databases using Google Cloud best practices. Who should take this course? Cloud engineers, database administrators, DevOps professionals, developers, and solution architects working with scalable, cloud-native applications.
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Build practical skills to design, scale, and operate globally distributed databases using Google Cloud Spanner. This course introduces Cloud Spanner fundamentals, including its distributed architecture, strong consistency, and ability to support mission-critical applications at global scale. You will learn how to analyze database capacity and usage patterns, design highly available and resilient database architectures, and implement secure connectivity and access management strategies. The course also covers monitoring, troubleshooting, and backup and recovery techniques to ensure operational reliability. In addition, you will explore how to optimize database cost and performance, automate database tasks, and design and implement data migration and replication strategies. Through hands-on demonstrations, you will evaluate backup and recovery processes, monitor database metrics, configure read replicas, and implement scaling strategies. By the end of this course, you will be able to design, deploy, and manage production-ready Cloud Spanner databases using Google Cloud best practices. Who should take this course? Cloud engineers, database administrators, DevOps professionals, solution architects, and developers working with scalable and distributed database systems.
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Build practical skills to design, optimize, and manage high-performance relational databases using Google Cloud AlloyDB. This course introduces AlloyDB fundamentals, including its PostgreSQL compatibility and support for hybrid transactional and analytical processing (HTAP) workloads. You will learn how to analyze database capacity and usage patterns, design highly available and resilient database architectures, and implement secure connectivity and access management strategies. The course also covers monitoring, troubleshooting, and backup and recovery techniques to ensure database reliability and operational continuity. In addition, you will explore how to optimize database cost and performance, automate database operations, and design data migration strategies for moving workloads to AlloyDB. Through hands-on demonstrations, you will evaluate machine configurations, compare deployment strategies, monitor database metrics, and perform backup and restore operations. By the end of this course, you will be able to design, deploy, and manage production-ready AlloyDB databases using Google Cloud best practices. Who should take this course? Cloud engineers, database administrators, DevOps professionals, developers, and solution architects working with relational databases and cloud-native applications.
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Build practical skills to design, manage, and scale large-scale NoSQL databases using Google Cloud Bigtable. This course introduces Bigtable fundamentals, including its distributed architecture and ability to handle high-throughput, low-latency workloads for real-time and analytical applications. You will learn how to analyze database capacity and usage patterns, design highly available and resilient database solutions, and implement secure connectivity and access management strategies. The course also covers monitoring, troubleshooting, and backup and recovery techniques to ensure database reliability. In addition, you will explore how to optimize database cost and performance, automate database operations, and design data migration solutions. Through hands-on demonstrations, you will learn how to add clusters, provision Bigtable instances, evaluate cost, and implement scaling strategies. By the end of this course, you will be able to design, deploy, and manage production-ready Bigtable databases using Google Cloud best practices. Who should take this course? Cloud engineers, database administrators, DevOps professionals, solution architects, and developers working with large-scale data systems.
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The Google Cloud SQL: Design, Deploy & Optimize Databases course is designed for cloud engineers, database administrators, DevOps professionals, and solution architects who want to design, deploy, and manage relational databases using Google Cloud SQL. This course provides a comprehensive introduction to Cloud SQL on Google Cloud Platform (GCP) and covers the core concepts required to deploy and manage scalable, highly available database solutions in the cloud. You will explore how Cloud SQL supports popular database engines such as MySQL, PostgreSQL, and SQL Server, and learn how to configure, monitor, and optimize database workloads in Google Cloud environments. The course begins with the fundamentals of Cloud SQL, including service architecture, supported database engines, and the different Cloud SQL editions available for enterprise deployments. You will then explore how to design reliable database solutions by implementing high availability, backup and recovery strategies, monitoring, and disaster recovery planning. You will also learn how to deploy and optimize Cloud SQL databases, configure secure connectivity and access management, automate database operations, and implement migration and replication strategies. Additionally, the course includes hands-on demonstrations that guide you through real-world database configuration tasks such as network security setup, storage selection, cost evaluation, and maintenance configuration. Through conceptual explanations, practical demonstrations, and real-world cloud engineering scenarios, this course helps you build the skills needed to effectively design, deploy, and optimize Cloud SQL databases in Google Cloud. The course includes approximately 4-10 hours of structured video content, organized into four weeks of learning, with quizzes and knowledge checks to reinforce key concepts. Enroll in Google Cloud SQL: Design, Deploy & Optimize Databases to gain practical experience managing relational databases in Google Cloud and confidently implement scalable, secure, and cost-optimized database solutions. Course Modules (Weekly Structure) Week 1: Cloud SQL Fundamentals and Course Introduction Week 1 introduces the fundamentals of Google Cloud SQL and provides an overview of the course structure and learning objectives. You will explore the core capabilities of Cloud SQL and understand how managed relational database services operate in Google Cloud. This week also covers supported database engines such as MySQL, PostgreSQL, and SQL Server, along with an introduction to Cloud SQL editions and deployment options. By the end of this week, you will understand the core architecture, features, and capabilities of Cloud SQL and how it supports enterprise database workloads in Google Cloud. Week 2: Designing and Managing Cloud SQL Solutions Week 2 focuses on designing reliable and scalable database solutions using Cloud SQL. You will learn how to analyze database capacity requirements, plan database usage, and evaluate different database architectures for various workloads. This week also covers high availability and disaster recovery strategies, database monitoring and troubleshooting techniques, and designing backup and recovery solutions to protect critical data. By the end of this week, you will be able to design resilient Cloud SQL deployments and implement effective monitoring and recovery strategies. Week 3: Deploying and Optimizing Databases in Google Cloud Week 3 focuses on deploying and optimizing Cloud SQL instances for performance, scalability, and cost efficiency. You will explore database connectivity methods, access management considerations, and security best practices. You will also learn how to optimize database performance and cost, automate database tasks, and implement data migration and replication strategies for moving workloads to Google Cloud. By the end of this week, you will be able to deploy scalable Cloud SQL databases and optimize them for enterprise workloads. Week 4: Hands-on Cloud SQL Configuration and Management Week 4 focuses on practical demonstrations and hands-on scenarios for managing Cloud SQL environments. You will learn how to configure network and security settings, select appropriate storage types such as SSD and HDD, and perform database import and export operations. This week also covers cost evaluation for different Cloud SQL configurations, maintenance window configuration, and selecting appropriate machine configurations for database workloads. By the end of this week, you will have a strong understanding of practical Cloud SQL configuration and operational management tasks. By the End of This Course, You Will Be Able To Understand the core concepts and architecture of Google Cloud SQL Identify supported database engines and choose appropriate Cloud SQL configurations Design highly available and resilient database solutions Implement backup, recovery, and disaster recovery strategies Configure secure database connectivity and access management Optimize database performance and cost in Google Cloud Automate database operations and management tasks Implement database migration and replication strategies Configure and manage Cloud SQL environments using best practices This course if for cloud engineers, database administrators, database engineers, data engineers and architects etc.