May 04 2021

AWS Certified Database - Specialty (DBS-C01)

AWS Certified Database - Specialty  (DBS-C01)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 86 Lessons (10h 9m) | Size: 3.32 GB

Introduction to AWS database technologies on a per-service basis in preparation for the AWS Certified Database Specialty (DBS-C01) exam

In this course, we'll explore workload-specific database design, discuss how different database types are best leveraged, and dive into services like RDS, Aurora, and DynamoDB. This course aims to provide the fundamentals required to pass the AWS Certified Database Specialty (DBS-C01) exam by introducing AWS database technologies on a per-service basis.

Throughout the course, we'll go over deploying AWS database resources, managing those resources, and migrating them to additional regions or database engines. We'll also cover monitoring and troubleshooting - discussing RDS and Aurora features like Performance Insights and Enhanced Monitoring - and how to perform investigations and minimize downtime, thereby increasing availability.

We'll also touch on using services like Redshift for data warehousing and analytical workloads, and discuss popular migration methodologies between engines and services (including lessons on both homogeneous and heterogeneous migrations using AWS Database Migration Service).

Going into the AWS Certified Database Specialty exam, it's important that students feel comfortable performing administrative tasks on database resourcees - including everything from configuring backups, to cross-region replication, to best-practice migration methodologies.

After completing this course, students will have the knowledge required to properly leverage various AWS database offerings, such as RDS, Aurora, Aurora serverless and global database, DynamoDB, Database Migration Service, and even services like Redshift and Neptune. Students will have a foundational understanding of which database service is best leveraged for a given workload, taking feature availability into account.

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