Description

Introduction

Automation and orchestration are critical to managing complex data workflows and ensuring timely, reliable data delivery. This course explores how to design automated and orchestrated Matillion ETL pipelines using job scheduling, conditional logic, parameterization, and external integrations. It’s ideal for teams seeking to reduce manual tasks and improve operational efficiency.

Prerequisites

• Familiarity with Matillion ETL (interface and job types)

• Basic understanding of ETL/ELT processes

• Knowledge of SQL and cloud data warehouse concepts (Snowflake, Redshift, BigQuery)

• Exposure to scripting or APIs (optional but helpful)

Table of Contents

1. Introduction to Automation and Orchestration
    1.1 Definitions and Key Differences
    1.2 Use Cases in Modern ETL Pipelines
    1.3 Automation Goals: Efficiency, Scalability, Reliability

2. Orchestration Job Design
    2.1 Using Orchestration Components
    2.2 Job Execution Control Flow
    2.3 Calling Transformation Jobs from Orchestration Jobs

3. Job Scheduling and Triggers
    3.1 Matillion’s Built-in Scheduler
    3.2 Time-based and Event-based Scheduling
    3.3 Triggering Jobs with API Calls or Webhooks

4. Parameterization and Variables
    4.1 Job Variables vs. Environment Variables
    4.2 Passing Parameters Dynamically
    4.3 Using Grid and Iterator Components for Loops

5. Conditional Logic and Error Handling
    5.1 IF Component and Switch Component
    5.2 Status and Error Return Codes
    5.3 Retry Patterns and Fallback Jobs

6. Building Reusable Modular Jobs
    6.1 Shared Job Design
    6.2 Parameterized Job Templates
    6.3 Reducing Redundancy and Increasing Maintainability

7. API-Driven Automation
    7.1 Using Matillion’s REST API
    7.2 Triggering Jobs from External Systems
    7.3 Integrating with CI/CD Pipelines

8. Notifications and Alerting
    8.1 Sending Email Notifications on Success/Failure
    8.2 Integration with Slack or Microsoft Teams
    8.3 Logging Job Outcomes to External Systems

9. Real-world Workflow Examples
    9.1 Daily Data Sync Automation
    9.2 Multi-source Ingestion Orchestration
    9.3 Conditional Data Processing Pipeline
    9.4 Orchestrating a Full Data Warehouse Refresh

10. Best Practices for Scalable Automation
    10.1 Designing for Failure Recovery
    10.2 Testing and Versioning Jobs
    10.3 Monitoring and Auditing Automation Workflows

Matillion’s automation and orchestration capabilities empower data teams to build scalable, reliable, and maintainable ETL pipelines. By leveraging job control structures, scheduling, parameterization, and API integration, organizations can streamline operations and respond dynamically to data events and business needs.