This applied, hands-on course teaches you how to manage the entire life cycle of models, whether they were created using a pipeline in Model Studio or using other software. In the first half of the course, you learn to use SAS Model Manager. In the second half of this course, you learn how to create business decisions based on rules and conditions that you author using your operational data through SAS Decision Manager. Your business decisions can be published for both batch and real-time web service execution.

The self-study e-learning includes:

• Annotatable course notes in PDF format.
• Virtual Lab time to practice.

Learn how to

• Manage SAS Model Manager data sources.
• Import models into SAS Model Manager.
• Score SAS Model Manager models.
• Create SAS Model Manager performance reports.
• Author and test business rules using SAS Decision Manager.
• Build business decisions in SAS Decision Manger.
• Use lookup tables in rules (self-study).

Who should attend

IT staff who are involved in data preparation and scoring; modelers who create and test models; and business analysts who are consumers of the model, as well as business analysts or consultants who are responsible for integrating models, business rules, and rule flows into operational processes

Formats available	Standard duration
Classroom:	1.0 day
Live Web Classroom:	2 half-day session(s)
e-Learning:	7 hours/180 day license

Before attending this course, you should be familiar with data mining concepts and predictive models. You should also have an introductory-level familiarity with basic data structures (denormalized tables), business rules, and models.

This course addresses SAS Model Manager, SAS Decision Manager software.

Making Decisions

• Data-based decisions.

Model Manager

• Introduction.
• Project setup.
• Importing models.
• Model properties.
• Evaluating models.
• Creating a model performance report.
• Importing, enabling, and using a workflow.

Decision Manager

• Introduction.
• Accessing data.
• Creating rule sets.
• Creating and testing decisions.
• Lookup table (self-study).