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Course Outline
Introduction
- Overview of AWS Glue and its core components
- Understanding AWS Glue components and architecture
- Benefits and limitations of AWS Glue
Working with 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 Transformation
- Applying transformations
- Resolving type choices
- Selecting and renaming columns
- Removing fields
- Using filters
- Using map functions
- Performing joins
- Unpivoting
- Flattening JSON structures
Understanding the Glue Workflow
- Working with Glue jobs
- Configuring triggers
Debugging
- Resolving script retrieval errors
- Fixing launch errors
- Correcting Glue argument errors
- Addressing policy errors
Summary and Next Steps
Requirements
- Familiarity with 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.