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
Financial institutions are entering a new phase in credit risk modeling. AI and machine learning are no longer experimental capabilities. They are becoming central to how risk is assessed, priced and managed at scale. At the same time, regulatory expectations are evolving. The European Central Bank (ECB) has opened the
Clinical trials are the most costly, time-consuming, and heavily regulated stages in drug development, often costing hundreds of millions of dollars and sometimes exceeding a billion dollars. Every month of delay cuts into the patent-protected window that determines a drug’s commercial viability, with companies losing tens of millions of dollars
As a Senior Lecturer in Finance at Massey University, one of New Zealand’s leading tertiary institutions, my role as an educator is to prepare students to thrive in a rapidly evolving, data-driven world. I have always believed that analytics education must strike a balance between technical capability and critical thinking,
Each year, the SAS Finance Analytics School (SAS FAS4S) brings students inside the real world of financial decisioning – far beyond what any classroom lecture can offer. It’s a rare chance to see how analytics, AI and fraud prevention actually work inside banks, public institutions, and regulatory environments. That’s what
En 2024, près d’une entreprise française sur deux a subi une cyberattaque majeure, et dans 60 % des cas, tout a commencé par un simple mail ou appel frauduleux. Derrière chaque clic, chaque voix clonée, l’ingénierie sociale exploite nos failles humaines pour contourner les défenses les plus sophistiquées. Phishing, deepfake, usurpation
En la era de la inteligencia artificial y el machine learning, el valor de los datos es incuestionable. Los modelos aprenden, predicen y toman decisiones a partir de los datos con los que son entrenados. Sin embargo, cuando los datos reales escasean o no pueden utilizarse por razones de privacidad,
Generative AI (GenAI) has moved past its experimental phase. It is now deeply embedded in core business workflows, from sophisticated financial modeling and predictive analytics to dynamic content creation and strategic decision-making. This means the very definition of a “job-ready” professional has dramatically changed. Global surveys reveal the same trend:
Think of data engineering as plumbing for the digital world. All those smart dashboards, AI models and analytics reports don’t work unless someone builds the pipelines that bring clean, usable data to them. That someone is a data engineer. Why data engineers are suddenly in the spotlight AI is everywhere today
If you have a background in pharmacy, life sciences, biotechnology, or statistics – and you’re curious about the world of clinical research – there’s one career path you might want to explore: clinical SAS programming. Maybe you’ve heard the term before and wondered what it really involves. The good news?
