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Course Outline
Introduction
- Overview of AWS Glue and its components.
- Understanding AWS Glue components and architecture.
- Benefits and limitations of AWS Glue.
Working with the Data Catalog
- Understanding AWS Glue crawlers and the data catalog.
- Creating a database.
- Creating a table.
- Working with crawlers.
- Building custom classifiers.
AWS Glue Development Endpoint
- Utilizing a development notebook.
- Understanding Glue context and dynamic frames.
- Creating a dynamic frame.
AWS Glue Transformations
- Applying transformations.
- Resolving choices.
- Selecting and renaming fields.
- Dropping fields.
- Using filters.
- Using maps.
- Performing joins.
- Using spigots.
- Flattening JSON.
Understanding the Glue Workflow
- Working with Glue jobs.
- Working with triggers.
Debugging
- Resolving script retrieval errors.
- Resolving launch errors.
- Resolving Glue argument errors.
- Resolving policy errors.
Summary and Next Steps
Requirements
- Familiarity with ETL (Extract, Transform, Load) concepts.
- Basic proficiency in Python programming.
Audience
- Data engineers.
- Data analysts.
14 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
