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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

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