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Public health systems are under pressure from rising costs, workforce shortages, increasing demand and limited resources. Data and AI can help organizations use their resources more effectively, improve care decisions and deliver better outcomes. But the next phase of health care AI will depend on more than what the technology
Rules-based decisioning engines (also known as enterprise decisioning applications) have long been a mainstay for marketers. These applications automate marketing actions using predefined business rules. When the decision is executed as part of a marketing campaign, specific conditions defined in the rules will trigger actions without requiring manual segmentation or
A previous article discusses the problem of fitting a kernel density estimate (KDE) to data that are strictly positive. If you use a standard KDE, the resulting density curve might estimate non-zero probability for negative values. This is unsatisfactory because quantities like lengths and mass cannot be negative. The previous
As SAS celebrates its 50th anniversary, one question naturally follows: What comes next? Few groups have a better vantage point than the partners who work alongside SAS every day. They help organizations apply analytics and AI across industries, giving them a front row seat to the challenges customers are trying
Explore how the DementAI team used SAS Viya's integrated AI, machine learning, governance, and decisioning capabilities to help identify Alzheimer's disease up to two years earlier while maintaining the trust and oversight required in healthcare.
Most conversations about agentic AI focus on how autonomous these systems can become. Financial services leaders are asking a different question: Where should autonomy stop? For banks and insurers, the challenge is not simply deploying AI agents. It is determining how those systems, governance requirements and human expertise can work
AI is reshaping how work gets done across industries. In marketing, the real challenge is turning a multitude of ideas into a final campaign. A typical campaign often starts with a strategy meeting, followed by sessions with data teams and creative reviews. Stakeholders weigh in at different stages, sometimes with
Learn how SAS 9 customers can modernize to SAS Viya incrementally, leveraging AI assistance, agentic AI, open-source collaboration, and scalable cloud deployment while preserving existing SAS investments and governance.
Is the roof over your head about to cave in? Did you just change jobs, get married or start planning for retirement? In situations like these, most people think about their insurance. Life changes are a great time to evaluate insurance coverage (for customers and insurance companies alike), but waiting
Editor’s note: This post was co-authored by Diana Rothfuss. For the past few years, banks have focused on proving that AI can deliver business value. Across financial services, organizations have launched pilots, explored generative AI use cases and tested how AI can improve everything from customer engagement and fraud detection
Organizations have spent years investing in data, analytics and AI. Many now have dashboards, predictive models and generative AI tools. Yet one challenge continues to surface: turning those insights into timely, consistent decisions. That’s one reason decision intelligence is getting more attention. As AI becomes part of everyday business, organizations
Mientras millones de personas siguen atentos cada partido, analizan alineaciones y debaten sobre las posibilidades de sus selecciones favoritas, existen diferentes factores cada vez más influyentes en los resultados dentro y fuera de la cancha: los datos, la Inteligencia Artificial (IA) y la analítica. El fútbol moderno ya no se
Many AI initiatives don’t stall because of the models – they stall because of the data behind them. Teams can build promising prototypes, but moving those models into production is where progress slows down. Data is spread across systems, pipelines are difficult to maintain and governance often lags behind how
The kernel density estimate (KDE) is a powerful tool for estimating the density of univariate data. The KDE is a flexible model. For example, it can fit data distributions that are multimodal or have long tails. It is nonparametric, which means that you do not need to assume any form
Every evolution in analytics raises a new question. Once one source of friction disappears, another becomes the opportunity. In the first blog in this series, we explored how SAS® Visual Analytics helps organizations move from data to decisions through interactive visualizations, advanced analytics and enterprise governance. In the second and