Course Overview
In this course, you will learn about the process of planning and designing both relational and nonrelational AWS databases. It will teach you how to use workload requirements to define database design considerations and also explore the features and capabilities of the eight AWS database services. By the end of the course, you will be able to determine which AWS database service is right for yourĀ workloads, andĀ design the database to meet your requirements.
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Who is it for?
The course isĀ aimed at:Ā
- Data engineersĀ
- Solutions architectsĀ
- DevelopersĀ
- IT professionals
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Entry Requirements
We recommend that attendees of this course have:Ā
- Familiarity with AWS Database Services, equivalent to AWS Database Offerings digital trainingĀ
- Understanding of database design concepts, and/or dataĀ modelingĀ for relational or nonrelational databasesĀ
- Familiarity with cloud computing conceptsĀ
- Familiarity with general networking and encryption conceptsĀ
- Understanding of the threeĀ VāsĀ of data (volume, velocity, and variety)Ā
- Familiarity with basic data analytics concepts, equivalent to Data Analytics Fundamentals digital trainingĀ
- Understanding of general architecting best practices and the AWS Well-Architected Framework, equivalent to Architecting on AWS classroom trainingĀ
The Exam
There is no exam for this courseĀ
Course Objectives
This course teaches you how to:Ā
- Apply database concepts, database management, and data modelling techniquesĀ
- Evaluate hosting databases on Amazon EC2 instancesĀ
- Evaluate relational AWS database services and their features (Amazon RDS, Amazon Aurora, and Amazon Redshift)Ā
- Evaluate nonrelational AWS database services and their features (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB)Ā
- Examine how the design criteria apply to each serviceĀ
- Apply management principles based on the unique features of each service Ā
Syllabus – Key points
The courseĀ syllabus and content is based upon:Ā
Day OneĀ
Module 1: Database concepts and general guidelinesĀ
- Databases in the cloudĀ
- Database design principlesĀ
- Transactional complianceĀ
Module 2: Database planning and designĀ
- Workload requirementsĀ
- Design considerationsĀ
Module 3: Databases on Amazon EC2Ā
- Amazon EC2 for hosting databasesĀ
Module 4: Purpose-built databases on Amazon EC2 and Amazon RDSĀ
- The journey to AWSĀ
- Data modelling basicsĀ
Module 5: Amazon RDSĀ
- Amazon RDS overviewĀ
- Amazon RDS distinguishing featuresĀ
- Amazon RDS design considerationsĀ
- Hands-on Lab: working with Amazon RDS databasesĀ
Module 6: Amazon AuroraĀ
- Amazon Aurora overviewĀ
- Amazon Aurora distinguishing featuresĀ
- Amazon Aurora design considerationsĀ
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Day TwoĀ
Module 6: Amazon Aurora (continued)Ā
- Hands-on Lab: working with Amazon Aurora databasesĀ
Module 7: Amazon DocumentDB (with MongoDB compatibility)Ā
- Amazon DocumentDB overviewĀ
- Amazon DocumentDB design considerationsĀ
- Amazon DocumentDB distinguishing featuresĀ
- Hands-on Lab: working with Amazon DocumentDB databasesĀ
Module 8: Amazon DynamoDBĀ
- Amazon DynamoDB overviewĀ
- Amazon DynamoDB data modellingĀ
- Amazon DynamoDB distinguishing featuresĀ
- Amazon DynamoDB design considerationsĀ
- Hands-on Lab: working with Amazon DynamoDBĀ
Day ThreeĀ
Module 9: Databases in Amazon NeptuneĀ
- Amazon Neptune overviewĀ
- Amazon Neptune design considerationsĀ
Module 10: Databases in Amazon Quantum Ledger Database (Amazon QLDB)Ā
- Amazon QLDB overviewĀ
- Amazon QLDB Design ConsiderationsĀ
Module 11: Databases in Amazon ElastiCacheĀ
- Amazon ElastiCache overviewĀ
- Amazon ElastiCache for MemcachedĀ
- Amazon ElastiCache for RedisĀ
Module 12: Data warehousing in Amazon RedshiftĀ
- Amazon Redshift overviewĀ
- Amazon Redshift distinguishing featuresĀ
- Amazon Redshift data modellingĀ
- Amazon Redshift design considerationsĀ
- Hands-on Lab: working with Amazon Redshift ClustersĀ
Module 13: Course OverviewĀ
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