Description

Introduction

This training provides a comprehensive, hands-on understanding of FME Workbench, enabling data engineers to design, transform, map, and automate complex ETL workflows without code. Participants learn how to work with spatial and non-spatial data, build scalable pipelines, integrate enterprise systems, and optimize performance for production-grade data operations.

Prerequisites

• Basic knowledge of data integration or ETL concepts

• Understanding of spatial or tabular data formats (optional but helpful)

• Familiarity with databases, GIS, or cloud platforms is an advantage

Table of Contents

1. Introduction to FME Workbench

 1.1 Overview of FME Platform
 1.2 Key Components: Workbench, Server, Data Inspector
 1.3 FME Interface, Navigation & Project Structure
 1.4 Understanding Readers, Writers & Transformers

2. Working with Data Sources

 2.1 Adding & Configuring Readers
 2.2 Adding & Configuring Writers
 2.3 Handling Spatial vs Non-Spatial Data
 2.4 Working with Common Data Formats (CSV, Excel, JSON, XML, Shapefile, GeoJSON)

3. Core Transformers for ETL

 3.1 Attribute Management Transformers
 3.2 Geometry Transformers
 3.3 String, Numeric & Conditional Transformers
 3.4 Schema Mapping & Reprojection

4. Building Complete ETL Pipelines

 4.1 Designing End-to-End ETL Flows
 4.2 Data Validation & Quality Checks
 4.3 Error Handling & Logging
 4.4 Best Practices for Pipeline Structure

5. Spatial Data Engineering with FME

 5.1 Working with Coordinate Systems
 5.2 Spatial Joins, Overlays & Buffering
 5.3 Spatial Data Cleaning & Enrichment
 5.4 Transformations for GIS Integration

6. Automation & Scheduling

 6.1 Automating Workflows with FME Server
 6.2 Scheduling & Event-Based Triggers
 6.3 Parameterizing Workflows
 6.4 Notifications & Monitoring

7. Advanced Data Integration

 7.1 Integrating with Cloud Platforms (AWS, Azure, GCP)
 7.2 Database Connections & SQL Integration
 7.3 API Integration & Web Services
 7.4 Handling Big Data with FME

8. Performance Optimization

 8.1 Improving Transformation Performance
 8.2 Parallel Processing & Batch Operations
 8.3 Memory Optimization Techniques
 8.4 Troubleshooting & Debugging

9. Real-World Use Cases & Scenarios

 9.1 Enterprise ETL Migration
 9.2 GIS-Centric Data Workflows
 9.3 Automated Data Validation Systems
 9.4 Multi-source Data Integration

10. Hands-On Projects

 10.1 Building a Data Conversion Pipeline
 10.2 Automating a Scheduled ETL Job
 10.3 Integrating Web APIs with Mapping Data
 10.4 Spatial Data Cleanup Project

This course equips data engineers with the skills to design robust ETL workflows using FME Workbench. Learners gain the expertise to automate processes, enhance data quality, and integrate multiple systems efficiently. The training prepares participants to confidently manage real-world enterprise data transformation tasks.