Pass the Google Cloud Professional Database Engineer Exam 

What you'll learn 

Choose appropriate types of database for use cases from relational, document, wide-column, and analytical databases 

Manage database users, security, and networking access 

Implement database migrations and change data capture solutions 

Optimized database performance through modeling, partitioning, clustering, and replicas 

Manage data using exports, imports, and backups 

Monitor databases and troubleshoot problems 

Requirements 

Some experience with cloud computing is helpful 

Description  

Databases are the foundation of many of the applications and services that we use every day. Keeping them up and running is the responsibility of database engineers. In this course, you will learn essential skills and hear hard-learned lessons about designing, deploying, securing, and maintaining highly scalable and highly available databases. By the end of the course, you'll be ready to take the Google Cloud Professional Database Engineer Exam and take on the responsibilities of a database engineer working in Google Cloud.The course begins with an introduction to relational databases and working with Cloud SQL, a regional, managed database service provided by Google Cloud. You will learn:When to use Cloud SQLHow to create a Cloud SQL database instanceManaging usersCreating, managing, and cloning databasesConnecting securely to your databasesBest practices for importing, exporting, and backing up your databasesWe'll also cover database maintenance and how to migrate a self-managed database to Cloud SQL. But we don't stop with Cloud SQL. Google Cloud offers AlloyDB, a scalable PostreSQL implementation that is designed to support both online transaction processing and analytical workloads. You will also learn about Cloud Spanner, the managed, globally scalable relational database offered by Google Cloud.In addition to relational databases, we dig into the details of BigQuery, a petabyte scale data warehouse, and analytics service. You'll learn how to use BigQuery's console to navigate datasets, organize data using partitioning and clustering, and control access to data in BigQuery. Bigtable and Cloud Firestore are two managed NoSQL databases available in Google Cloud. In this course, you'll see how to create Bigtable databases, add clusters to a Bigtable instance, and design multidimensional schemas that are highly performant in Bigtable. You'll also learn about Cloud Firestore, a document database, that provides flexible schemas while also offering indexing and a query language that makes it an ideal choice for a database backend for many services.In addition to knowing about different kinds of databases and when to use them, database engineers have to maintain and troubleshoot databases. This course will help you learn how to estimate the size of databases, monitor databases as well as configure security and networking for databases. You'll also learn about essential data management practices including change data capture (CDC) using Datastream and database migration using Database Migration Service.Database engineers are in demand because they understand how to build, deploy, and manage critical information infrastructure. Google Cloud has developed the Professional Cloud Database Engineer certification to distinguish database engineers with the necessary skills to operate high-performance databases in production environments in Google Cloud. Join us in this course to advance your career as a certified Professional Database Engineer. 

Overview 

Section 1: Introduction 

Lecture 1 Introduction 

Lecture 2 First Look at Google Cloud 

Lecture 3 How to Get Help If You Are Stuck 

Section 2: Getting Started with Cloud SQL 

Lecture 4 Introduction to Relational Databases 

Lecture 5 When to Use Cloud SQL 

Lecture 6 Creating a PostgreSQL Instance 

Lecture 7 Adding and Deleting Users in Cloud SQL 

Lecture 8 Cloning a Cloud SQL Database 

Lecture 9 Deleting a Cloud SQL Instance 

Lecture 10 Estimating the Cost of A Cloud SQL Database 

Section 3: Cloud SQL Auth Proxy and SSL 

Lecture 11 Overview of Cloud SQL Auth Proxy 

Lecture 12 Installing Cloud SQL Auth Proxy 

Lecture 13 Using SSL with Cloud SQL 

Section 4: Additional Cloud SQL Functionality 

Lecture 14 Importing and Exporting with Cloud SQL 

Lecture 15 Best Practices for Importing and Exporting Data with Cloud SQL 

Lecture 16 Replication in Cloud SQL 

Lecture 17 Creating a Read Replica in Cloud SQL 

Lecture 18 Creating Cloud SQL Backups 

Lecture 19 Cloud SQL Maintenance 

Lecture 20 Database Migration Service 

Lecture 21 Using gcloud Commands with Cloud SQL 

Section 5: AlloyDB 

Lecture 22 Overview of AlloyDB 

Lecture 23 Creating and AlloyDB Instance 

Lecture 24 Estimating the Cost of AlloyDB Databases 

Section 6: Cloud Spanner 

Lecture 25 When to Use Cloud Spanner 

Lecture 26 Creating a Cloud Spanner Instance 

Lecture 27 Creating a Database and Tables in Cloud Spanner 

Lecture 28 Adding Users to Cloud Spanner 

Lecture 29 Deleting a Cloud Spanner Instance 

Lecture 30 Cloud Spanner Change Streams 

Lecture 31 Exporting Data from Cloud Spanner 

Lecture 32 Importing Data to Cloud Spanner 

Lecture 33 Cloud Spanner Performance Considerations 

Lecture 34 Estimating the Cost of Cloud Spanner Instances 

Section 7: BigQuery 

Lecture 35 Introduction to BigQuery 

Lecture 36 Navigating and Querying BigQuery Datasets 

Lecture 37 Loading Data into BigQuery 

Lecture 38 Partitioning and Clustering BigQuery Tables 

Lecture 39 Access Controls in BigQuery 

Lecture 40 Estimating the Cost of BigQuery 

Section 8: Firestore 

Lecture 41 Firestore and Document Databases 

Lecture 42 Create a Collection in Firestore 

Lecture 43 Firestore Indexes 

Lecture 44 Firestore Importing and Exporting 

Lecture 45 Estimating the Cost of a Firestore Database 

Section 9: Bigtable 

Lecture 46 Introduction to Bigtable 

Lecture 47 Creating a Bigtable Instance 

Lecture 48 Creating a Table in Bigtable 

Lecture 49 Adding a Cluster to a Bigtable Instance 

Lecture 50 Designing Bigtable Row Keys 

Lecture 51 Denormalization Patterns in Bigtable 

Lecture 52 Deleting a Bigtable Instance 

Lecture 53 Bigtable App Profiles 

Lecture 54 Estimating the Cost of Bigtable 

Section 10: Database Operations 

Lecture 55 Roughly Estimate Database Size 

Lecture 56 More Precisely Estimate Relational Database Size based on Database Platform 

Lecture 57 Monitoring and Alerting 

Lecture 58 Database Security Best Practices 

Lecture 59 Datastream and Change Data Capture 

Lecture 60 IP Addressing 

Lecture 61 Private Service Connect 

Section 11: Conclusions 

Lecture 62 Exam Tips and Strategies 

Lecture 63 Additional Resources 

Lecture 64 Concluding Remarks 

Section 12: Practice Exam 

Database administrators,Database engineers,Data modelers,Database developers,Cloud engineers,Data engineers,Data analysts,Application developers,Software engineers