This repository contains demos for specific industry use cases on SAS Viya Workbench. Demos are organised in different folders as per industry.
We hope these demos stimulate thoughts and ideas around possibilities with SAS Viya Workbench, a developer-oriented, scalable and performant analytics environment which increases productivity. This repository is also an ideal platform for you to showcase your demos (planned) and collaborate with like-minded creators.
Refer here for the full list of demos. Additional demos are expected to be added to this repo soon after following a review process. We highlight the following demos:
| Name | Brief Description | Industry | Owner/Contact | Components | Last Update |
|---|---|---|---|---|---|
| Loan Default Model | Fit, assess and compare predictive models for loan defaults | Banking | [email protected] | SAS, Python | 21NOV2024 |
| Modeling for Pulmonary Fibrosis Progression | Coding examples in SAS for predicting pulmonary fibrosis progression using anonymized patient data | Health & Life Sciences | [email protected] | SAS | 13MAR2025 |
| Diabetes Prediction through Python Classes | Predict for diabetes using a Python class through an Object-oriented Programming paradigm | Health & Life Sciences | [email protected] | Python | 17APR2025 |
Make use of a SAS Viya Workbench environment and clone this repository using Git integration capabilities within the Visual Studio Code editor or Jupyter Lab/ Jupyter Notebook interface. You can also use alternative download mechanisms or download / access only a specific demo folder. All demos are self-contained within their respective folders.
git clone https://github.com/sassoftware/sas-viya-workbench-demos
At present, we accept contributions to this repository only from contributors within the SAS Software organisation. As this project evolves, we will consider contributions from a wider audience. Refer to the Contributing.md page for more details.
This project is licensed under the Apache 2.0 License.
- Sundaresh Sankaran ([email protected] / [email protected])
- Yi Jian Ching