Reporting Scenario Activities
Automating the Model Lifecycle
Use metrics, checks, and scenarios to schedule jobs and monitor the lifecycle of a data project
The lifecycle of a data project doesn’t end once a Flow is complete. It’s not possible to Dev/Test a model until it’s perfect because data is ever changing. At the same time, ensuring that your data and models are up-to-date is something that you don’t want to have to do manually. Dataiku DSS has automation features to help with this.
In this course, you will learn the basics of:
- Scheduling jobs using scenarios
- Monitoring jobs
- Monitoring the status and quality of your dataset