SAS Visual Data Mining — Predict Trends
SAS Visual Data Mining & Machine Learning is a model building and data analysis platform for enterprise data teams
SAS Visual Data Mining & Machine Learning provides a comprehensive environment for data scientists and analysts to build sophisticated predictive models using a visual or coding interface. This platform is designed specifically for enterprise-level organizations that need to manage the entire analytics lifecycle from data preparation to model deployment. By integrating data mining and machine learning within a single scalable engine, the tool allows teams to process massive datasets without technical bottlenecks. The platform streamlines the creation of complex models through an interactive, drag-and-drop interface while still supporting specialized code in languages like Python and R. SAS Visual Data Mining & Machine Learning includes automated feature engineering and hyperparameter tuning to ensure that models are both accurate and efficient. Business owners can find more details on how to integrate these solutions at surfai.app to improve their data-led decision-making processes. Main use cases include fraud detection in financial services, demand forecasting for retail inventory, and predictive maintenance for manufacturing equipment. The software also offers advanced natural language processing and computer vision capabilities for analyzing unstructured data types. These features enable businesses to extract value from images and text alongside traditional structured data. Access is typically provided via enterprise licensing agreements based on specific business requirements. Prospective users can explore the software through the SAS Viya free trial period to test the visual interface and processing capabilities before committing to a full deployment.
- Pricing: enterprise
Specifications
| Pricing | enterprise |
|---|---|
| Integrations | Python, R Studio, JupyterLab, Amazon S3, Microsoft Azure, Snowflake, Google Cloud Platform, Hadoop |
| Best for | data-scientists, enterprise-executives, business-analysts, security-teams |
| Website status checked | 2026-10-24T06:00:40.83+00:00 |
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