The SAS Data Science Blog
Advanced analytics from SAS data scientists
Authors: Shahrzad Azizzadeh, Kaustubh Khandwe, Bahar Biller, and Paul Venditti On large-scale solar farms, power loss is the silent drain on profits. Unoptimized panels chip away at efficiency, causing hidden losses that people often overlook—but those losses are never insignificant. In this post, we’ll uncover how to spot and solve these
Learn how public health agencies can streamline analytic software costs by assessing tool usage, infrastructure, and licensing, and by leveraging SAS Viya’s cloud-based capabilities to improve efficiency and collaboration amid budget constraints.
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.