Matillion Tutorial

Matillion is a powerful, cloud-native ETL/ELT tool built specifically for modern cloud data warehouses like Snowflake, Amazon Redshift, and Google BigQuery. It simplifies data integration, transformation, and orchestration with a low-code visual interface, making it easy for data teams to automate complex workflows.

Why Use Matillion?

• Native support for cloud platforms (AWS, Azure, GCP)
• No infrastructure management
• Drag-and-drop workflow builder
• Easy integration with APIs, databases, and files
• Built-in components for transformation, scripting, and orchestration
• Secure and scalable

Matillion Architecture Overview

Matillion follows an ELT (Extract, Load, Transform) approach where data is:

1. Extracted from sources (e.g., Salesforce, MySQL, S3)
2. Loaded into the cloud data warehouse
3. Transformed using SQL inside the warehouse for high performance

Supported Platforms:

• Matillion ETL for Snowflake
• Matillion ETL for Amazon Redshift
• Matillion ETL for Google BigQuery
• Matillion Data Loader (SaaS)

Getting Started with Matillion

Step 1: Launch Matillion Instance

• Available on AWS Marketplace, Azure Marketplace, and GCP Marketplace.
• Deploy an EC2 instance or use Matillion SaaS (Data Loader).
• Access the web interface using the instance IP.

Step 2: Connect to Your Cloud Data Warehouse

• Provide credentials for Snowflake, Redshift, or BigQuery.
• Test the connection.
• Configure default database/schema/project.

Understanding Matillion Components

1. Orchestration Jobs

Used to load and control data from external sources. Common components include:

• S3 Load
• API Query
• Python Script
• SQL Script
• Run Transformation

2. Transformation Jobs

Used to clean, aggregate, and transform data inside the cloud data warehouse. Components include:

• Join
• Filter
• Aggregate
• Calculator
• Rank
• Table Input/Output

Creating Your First Matillion ETL Job

Example Use Case: Load Sales Data from S3 → Snowflake → Clean → Aggregate

Step 1: Orchestration Job

• Add S3 Load Component:
  • Source: S3 bucket
  • Target: Snowflake staging table
• Use SQL Script: Create target table if needed.
• Run Transformation: Link to a transformation job.

Step 2: Transformation Job

• Input Table: Use staging table.
• Filter Rows: Remove NULL or test records.
• Calculator: Create new columns like Total = Qty * Price.
• Aggregate: Sum sales by region.
• Output Table: Save results in a reporting table.

Also Read: Matillion Interview Questions

Matillion Connectors & Integrations

Matillion supports 100+ connectors for:

• Databases: MySQL, PostgreSQL, Oracle, SQL Server
• Cloud Storage: Amazon S3, Azure Blob, Google Cloud Storage
• SaaS: Salesforce, HubSpot, Shopify, Marketo, Google Ads
• APIs: REST API integration using API Query component

Matillion vs Traditional ETL Tools

 Security and Governance

• Role-based access control (RBAC)
• Integration with AWS IAM, Azure AD, GCP IAM
• Audit logs for job runs
• Encryption at rest and in transit
• SOC2 and GDPR compliance

Scheduling and Automation

• Use built-in Schedulers to run jobs at specific times.
• Trigger jobs via API calls or other orchestration tools.
• Integrate with Airflow, dbt, CI/CD pipelines using webhooks.

Matillion Best Practices

• Reuse transformation components via shared jobs
• Always separate orchestration and transformation
• Leverage variables for environment-specific configurations
• Use job variables and grid variables for dynamic execution
• Monitor job status with the Task History panel

Sample Use Cases

1. Data Warehouse ETL
   Source: Salesforce → Target: Snowflake → Transformation: Deduplicate contacts
2. Marketing Analytics
   Google Ads + Facebook Ads → BigQuery → Blend data → Weekly dashboard refresh
3. Retail Pipeline
   CSV files from FTP → Load to Redshift → Clean → Join with product catalog
4. API Ingestion
   REST API (JSON) → API Query → Extract → Flatten JSON → Store in Snowflake

Matillion Sample SQL Script Component

sql

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CREATE OR REPLACE TABLE sales_summary AS SELECT region, SUM(sales_amount) AS total_sales FROM sales_data GROUP BY region;

Use this SQL in a SQL Script Component in a transformation job.

Who Should Learn Matillion?

• Data Engineers
• BI Developers
• Data Analysts
• Cloud Architects
• ETL Developers transitioning to ELT

Matillion Certification & Learning Paths

• Matillion Academy – Official self-paced training
• Snowflake + Matillion Hands-on Projects
• Matillion Essentials Certification
• Google Cloud Looker + Matillion Stack Courses

Conclusion

Matillion is an efficient, scalable, and modern ETL/ELT platform tailored for cloud data ecosystems. It’s ideal for businesses looking to streamline their data pipelines without heavy scripting. With its visual approach and deep integrations, Matillion makes data transformation simple, fast, and powerful.

Whether you’re just starting your data engineering journey or looking to master Matillion for professional growth, this tutorial is your foundation.