The SAS Data Science Blog
Advanced analytics from SAS data scientists
In high-risk industries like construction and manufacturing, worker safety isn’t just a priority; it’s a constant challenge. Fast-moving environments, heavy machinery, and human unpredictability make it incredibly tough to monitor compliance and catch dangerous behavior before it leads to injury. As data scientists, we wanted to tackle that challenge head-on.
Authors: Subbu Pazhani and Rob Pratt Large-scale real-world optimization problems with advanced business rules are often difficult to solve with standalone traditional optimization algorithms. Metaheuristic algorithms often complement these traditional optimization techniques. These are a class of powerful and flexible algorithms designed to address complex optimization problems, which traditional methods
SAS empowers modern demand planners with AI-driven tools like SAS Visual Forecasting and SAS Intelligent Planning to meet rising customer expectations through accurate, responsive, and scalable demand planning solutions.
SAS Viya now includes built-in bias mitigation in its machine learning procedures to help users develop ethical and trustworthy AI models by automatically detecting and reducing bias during training.
SAS is transforming the motor insurance claims process by integrating of tools - blending data management, ML, and UX into 1 complete system.
A practical guide to SAS Procedures in Viya 4, introducing their purpose, showcasing real-world examples, and highlighting a new downloadable cheat sheet that simplifies navigation across SAS’s advanced analytics portfolio.