Share Description
In this course, you will :
- When working with data services on the Amazon cloud, consider your storage and framework options.
- assists you in navigating the options for file storage, relational and NoSQL data storage, data warehousing, graph and ledger databases, and data lakes.
- Learn how to run open-source processing tools like Hadoop and Spark on AWS and take advantage of new serverless data services like Athena serverless queries and Aurora Serverless, an auto-scaling version of the Aurora relational database service.
Syllabus :
1. AWS Data Services Overview
- Use Amazon Web Services (AWS) data services
- Why use AWS data storage services?
- Explore file and HDFS storage
- Explore AWS data storage
- Understand why AWS Cloud tools matter
2. Storage and Files with S3 and More
- Explore the core file storage choices
- Explore AWS S3
- Explore AWS S3 using AWS CLI
- Explore AWS Glacier storage
- Explore AWS EBS and EFS
- Understand file import dervices for AWS and compare file services
3. SQL Databases with RDS
- Explore AWS RDS for managed RDBMS
- Explore AWS RDS MySQL
- Explore AWS RDS Aurora Serverless
- Use RDS query editor
4. NoSQL Databases with DynamoDB and More
- Explore NoSQL options in AWS
- Understand AWS ElastiCache
- Explore AWS DynamoDB
- Use AWS CLI with AWS DynamoDB
- Explore AWS DocumentDB
5. Data Warehouse and Pipelines with Redshift
- Explore the AWS data warehouse options and Redshift
- Work with AWS Redshift
- Connect to AWS Redshift with AWS query editor
- Visualize data with AWS QuickSight
6. Graph Databases and Ledgers with Neptune DB or QLDB
- Explore AWS specialty databases including graph and ledger
- Explore graphs with AWS Neptune
- Explore ledgers with AWS QLDB
- Explore event databases including Amazon Timestream
7. Hadoop and Spark with EMR
- Explore Hadoop and Spark on AWS
- Understand Hadoop jobs and libraries
- Explore AWS EMR with Hadoop and Spark
- Run Spark job on a Jupyter Notebook on AWS EMR
8. Data Lake with AWS Services
- Understand a data lake pattern with AWS Lake Formation
- Explore AWS Athena
- Explore AWS Glue Data Catalog and Crawlers
- Use AWS Glue for ETL
- Explore a data lake pattern with AWS Lake Formation
