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Course Outline
Introduction
- Overview of AWS Glue and its key components
- Insight into 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 databases
- Creating tables
- Operationalizing crawlers
- Developing custom classifiers
AWS Glue Development Endpoint
- Utilizing development notebooks
- Understanding Glue context and dynamic frames
- Creating dynamic frames
AWS Glue Transformation
- Applying transformations
- Resolving choices
- Selecting and renaming fields
- Dropping fields
- Filtering data
- Mapping data
- Joining datasets
- Processing data via spigots
- Flattening JSON structures
Understanding the Glue Workflow
- Managing Glue jobs
- Configuring triggers
Debugging Techniques
- Rectifying script retrieval errors
- Resolving launch errors
- Addressing Glue argument errors
- Fixing 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.