[center]Published 11/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.19 GB | Duration: 3h 51m

Pass the Google Cloud Professional Database Engineer Exam[/center]

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

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