This course provides a hands-on tour of the forecasting functionality in Model Studio, a component of SAS Viya. The course begins by showing how to load the data into memory and visualize the time series data to be modeled. Attribute variables are introduced and implemented in the visualization. The course then covers the essentials of using pipelines for generating forecasts and selecting champion pipelines in a project. It also teaches you how to incorporate large-scale forecasting practices into the forecasting project. These include the creation of data hierarchies, forecast reconciliation, overrides, and best practices associated with forecast model selection.
Learn how to
- Automatically create and fit custom forecast models using structured analytic workflows or pipelines.
- Visualize modeling data using attribute variables.
- Refine forecast models to improve forecast accuracy.
- Apply overrides-generated forecasts.
- Generate forecast data sets for deployment.
- Build and share custom pipelines for large-scale forecasting analyses.
Who should attend
Forecasters and analysts in any industry, including retail, financial services, manufacturing, and pharmaceuticals
Before attending this course, you should have an understanding of basic statistical concepts. You can gain this experience by completing the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course. Programming experience is not required.
This course addresses SAS Visual Forecasting software.
