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Machine Lerning Engineer
This course 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 your workloads, and design the database to meet your requirements.
1. Database concepts and general guidelines
- Databases in the cloud
- Database design principles
- Transactional compliance
2. Database planning and design
- Workload requirements
- Design considerations
3. Databases on Amazon EC2
- Amazon EC2 for hosting databases
4. Purpose-built databases databases on Amazon EC2 and Amazon RDS
- The journey to AWS
- Data modeling basics
5. Amazon RDS
- Amazon RDS overview
- Amazon RDS distinguishing features
- Amazon RDS design considerations
- Hands-on Lab: Working with Amazon RDS databases
6. Amazon Aurora
- Amazon Aurora overview
- Amazon Aurora distinguishing features
- Amazon Aurora design considerations
- Hands-on Lab: Working with Amazon Aurora databases
7. Amazon DocumentDB (with MongoDB compatibility)
- Amazon DocumentDB overview
- Amazon DocumentDB design considerations
- Amazon DocumentDB distinguishing features
- Hands-on lab: Working with Amazon DocumentDB databases
8. Amazon DynamoDB
- Amazon DynamoDB overview
- Amazon DynamoDB data modeling
- Amazon DynamoDB distinguishing features
- Amazon DynamoDB design considerations
- Hands-on Lab: Working with Amazon DynamoDB
9. Databases in Amazon Neptune
- Amazon Neptune overview
- Amazon Neptune design considerations
10. Databases in Amazon Quantum Ledger Database (Amazon QLDB)
- Amazon QLDB overview
- Amazon QLDB Design Considerations
11. Databases in Amazon ElastiCache
- Amazon ElastiCache overview
- Amazon ElastiCache for Memcached
- Amazon ElastiCache for Redis
12. Data warehousing in Amazon Redshift
- Amazon Redshift overview
- Amazon Redshift distinguishing features
- Amazon Redshift data modeling
- Amazon Redshift design considerations
- Hands-on Lab: Working with Amazon Redshift Clusters
- Applying database concepts, database management, and data modeling techniques
- Examining hosting databases on Amazon EC2 instances
- Examining relational AWS database services and their features (Amazon RDS, Amazon Aurora, and Amazon Redshift)
- Examining nonrelational AWS database services and their features (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB)
- Examining how the design criteria apply to each service
- Applying management principles based on the unique features of each service
Instructor-led training, hands-on labs, demonstrations, and group exercises.
This course is intended for the following job roles:
- Solution Architect
- Developer
- DevOps
- Data Analytics
Requirements:
- Familiarity with AWS Database Services, equivalent to AWS Database Offerings digital training
- Understanding of database design concepts, and/or data modeling for relational or nonrelational databases
- Familiarity with cloud computing concepts
- Familiarity with general networking and encryption concepts
- Understanding of the three V's of data (volume, velocity, and variety)
- Familiarity with basic data analytics concepts, equivalent to Data Analytics Fundamentals digital training
- Understanding of general architecting best practices and the AWS framework
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