Treasure Workflow allows you to define an object that can be made up of several queries, scripts, and machine learning algorithms. Additionally, you can schedule workflows to run according to your business needs. If you are new to Treasure Workflow, you might want to review our quick start tutorial.
- About Treasure Workflow
- Getting Started with Treasure Workflow
- TD Workflow Videos
- Using Treasure Workflow
- Workflow Reference
- Treasure Workflow Prerequisites and Limitations
- Workflow Processing States
- Workflow Control and Functional Operators
- Reference for Network Operators
- Reference for Treasure Data Operators
- Reference for Amazon Web Services Operators
- Reference for Google Cloud Platform Operators
- Workflow Built In Variables Reference
- Workflow and Continuous Deployment Examples
- Custom Scripts
- Introduction to Custom Scripts
- Adding a Custom Python Script to Your Workflow
- Workflow py Operator Syntax Reference
- Passing Parameters to Custom Scripts used in TD Workflow
- Custom Scripts Docker Image Versioning
- Custom Scripting Examples
- TD Python Spark Driver with Databricks
- TD Python Spark Driver with Google Colab
- TD Python Spark Driver with Amazon EMR
- Machine Learning