Description
This course is about AWS Glue Studio – A Server less ETL Framework.
AWS Glue is a server less data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. AWS Glue provides all the capabilities needed for data integration so that you can start analyzing your data and putting it to use in minutes instead of months.
This course is useful for,
- ETL Developers
- Data Engineers
- ETL Architects
- Data Migration Specialists
- Database Administrators
- Database Developers
Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products.
AWS Glue supports the following data sources:
¤Data stores
¤Amazon S3
¤Amazon Relational Database Service (Amazon RDS)
¤Third-party JDBC-accessible databases
¤Amazon DynamoDB
¤MongoDB and Amazon DocumentDB (with MongoDB compatibility)
¤Data streams
¤Amazon Kinesis Data Streams
¤Apache Kafka
AWS Glue Studio is a new graphical interface that makes it easy to create, run, and monitor extract, transform, and load (ETL) jobs in AWS Glue. You can visually compose data transformation workflows and seamlessly run them on AWS Glue’s Apache Spark-based server less ETL engine. You can inspect the schema and data results in each step of the job.