Description

Introduction

As data volumes and complexity grow, optimizing ETL performance becomes essential for efficient pipeline execution and cost control. This course is focused on enhancing the speed, scalability, and efficiency of ETL jobs in Matillion. It covers performance tuning techniques, best practices, and monitoring tools to help you build high-performance data pipelines.

Prerequisites

• Basic to intermediate knowledge of Matillion ETL

• Experience with SQL

• Familiarity with cloud data warehouses (Snowflake, Redshift, BigQuery)

• Understanding of general ETL/ELT workflows

Table of Contents

1. Understanding Performance in ETL Workflows
    1.1 Performance Metrics in Matillion
    1.2 ETL vs. ELT Performance Factors
    1.3 Identifying Bottlenecks

2. Optimizing Job Design
    2.1 Efficient Use of Transformation Components
    2.2 Reducing Component Complexity
    2.3 Job Splitting and Modularization

3. Data Volume Management
    3.1 Batch Size Considerations
    3.2 Filtering Early in the Pipeline
    3.3 Incremental Data Loads

4. SQL Pushdown Optimization
    4.1 Enabling SQL Pushdown
    4.2 Avoiding Memory-bound Operations
    4.3 SQL Best Practices for ELT

5. Performance Tuning per Cloud Platform
    5.1 Snowflake-Specific Optimization Tips
    5.2 Redshift-Specific Optimization Tips
    5.3 BigQuery-Specific Optimization Tips

6. Parallelization Techniques
    6.1 Using Parallel Iterator and Grid Iterator
    6.2 Executing Parallel Sub-Jobs
    6.3 Load Distribution Best Practices

7. Warehouse/Compute Management
    7.1 Right-sizing Virtual Warehouses
    7.2 Auto-suspend and Scaling Policies
    7.3 Monitoring Warehouse Utilization

8. Logging and Monitoring Tools
    8.1 Interpreting Job Duration and Logs
    8.2 Using Matillion’s Task History
    8.3 Third-party Monitoring Integration

9. Error Prevention and Retry Design
    9.1 Designing for Resilience
    9.2 Graceful Failure Handling
    9.3 Retry Loops for Intermittent Failures

10. Best Practices and Anti-patterns
    10.1 Common Performance Pitfalls
    10.2 Checklist for Optimized ETL Design
    10.3 Maintaining Long-term Performance

Performance optimization in Matillion ETL is not just about faster jobs—it’s about designing scalable, efficient, and maintainable data pipelines that meet business SLAs. By applying the techniques in this course, you’ll ensure your Matillion environment delivers high throughput, cost-effective data processing, and robust data delivery performance.