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Course Outline
Introduction
- Overview of AWS Glue and its components
- Understanding the AWS Glue components and architecture
- AWS Glue benefits and limitations
Working with Data Catalog
- Understanding AWS Glue crawlers and data catalog
- Creating a database
- Creating a table
- Working with crawlers
- Building custom classifiers
AWS Glue Development Endpoint
- Using a development notebook
- Understanding Glue context and dynamic frames
- Creating a dynamic frame
AWS Glue Transformation
- Applying transformations
- Resolving data type choices
- Selecting and renaming fields
- Dropping fields
- Filtering data
- Mapping data
- Joining data sets
- Capping data
- Flattening JSON
Understanding the Glue Workflow
- Working with Glue jobs
- Working with triggers
Debugging
- Fixing script retrieval errors
- Fixing launch errors
- Fixing Glue argument errors
- Fixing policy errors
Summary and Next Steps
Requirements
- Knowledge of ETL concepts
- Basic proficiency in Python programming
Target 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.