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.
From transforming online insurance services to combating the opioid epidemic, SAS customers are using data and AI to drive innovation, enhance efficiency and make a positive impact on society. These stories – and more – offer a glimpse into how our customers are shaping the future with SAS. Dive into
Learn how to modernize legacy SAS workflows by integrating Python and automating processes using GitHub Actions and SAS Viya Workbench, enabling seamless collaboration and CI/CD across development environments.
Every AI success story starts with a single decision: to move beyond experimentation and commit to real-world impact. But moving from idea to enterprise-scale deployment isn’t just about algorithms – it’s about laying the right groundwork. In the first part of this series, we explored three ways to lay the
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.
AI agents take on more responsibility in our most sensitive systems – from finance to public safety to health care – one thing is clear: trust can’t just be designed in. It has to be sustained. Continuously. In the first two parts of this series, we explored the ethical foundations
At SAS Innovate in Orlando, some of our partners spoke firsthand about how they’re driving innovation and delivering results with SAS®. In the video above, leaders from across our partner ecosystem offer insights into how collaboration, innovation and analytics are coming together to solve complex challenges and deliver results that
AI is transforming every industry, from automating insurance claims to optimizing supply chains in manufacturing. But for many organizations, the challenge isn’t whether to adopt AI; it’s how to start. This blog, the first in a two-part series, outlines the initial steps you can take to deliver a strong foundation for
Authors: Madhuri Kulkarni, Anand Surana, and Sudeshna Guhaneogi Imagine skipping the hours-long wait for your favorite amusement park ride by knowing when peak riding times are? Or how about having an itinerary that accounts for everyone’s favorite park activity? Ready for a wild ride? In this post, we explore how
My colleague Rick Wicklin maintains a nifty chart that shows the timeline of SAS releases since Version 8. A few of you asked if I could post a similar chart for SAS Enterprise Guide. Here it is. Like Rick, I used new features in SAS 9.4 to produce this chart
At SAS Innovate, attendees saw something they might not have expected. Amongst conversations about data, AI and enterprise transformation, they found themselves doing basketball drills. Real ones. With former Orlando Magic guard Cole Anthony at the center. Powered by SAS technology. And created by an unconventional duo of R&D and
The first leg of SAS Innovate on Tour has wrapped and what a journey it has been. These initial stops have set the tone for a year of innovation. Each recap below captures the energy and insights from the events so far, offering a glimpse into how data and AI
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
Let’s be real: no single language rules the world anymore. It’s all about the right tool for the job. You’ve seen the lists: “Top Programming Languages of 2024.” “Python vs. Rust: The Ultimate Showdown.” “Why Java Refuses to Die.” But you rarely see SAS on these lists. And I get
AI는 비즈니스와 기술 분야에서 여전히 가장 뜨거운 주제이지만, 아직 AI를 효과적으로 활용하여 가치를 창출하는 데에는 어려움이 많습니다. 여기 여러분의 능력을 발휘할 기회가 있습니다. 제 5회 'SAS 해커톤'에 참여하시고 최신 AI 기술을 활용한 가치 창출에 도전해 보세요! *SAS 해커톤 참가등록 : 등록 링크* 지금부터 8월 31일까지 등록할 수 있는 이번 해커톤은
Agentic AI is more than just the next step in automation. It’s a shift toward systems that don’t just respond to commands – they reason, decide and act with a blend of analytics and embedded governance. This is the second blog post in a series exploring how to design AI
AI is only as powerful as the data behind it. You’ve probably heard the phrase “garbage in, garbage out.” That’s always been true in analytics, but in today’s AI-driven world, the consequences of poor data are greatly amplified. Flawed models, biased predictions and opaque decision-making all trace back to one
When creative minds come together to solve real-world problems using the power of analytics, great things happen. The SAS Hackathon is more than just a competition; it’s a global innovation experience that brings together coders, domain experts and big thinkers from across industries and backgrounds. What we’ve been up to
여러분이 생각하시는 데이터와 AI의 미래는 어떤 모습인가요? 생성형 AI에서 양자 컴퓨팅까지, 지금껏 상상해왔던 수많은 기술과 개념이 지금 이 순간 현실로 다가오고 있습니다. 불가능을 가능으로, 상상을 현실로 만들 데이터와 AI의 첨단 화두가 무엇인지 궁금하시다면 SAS Innovate 2025에서 확인해 보세요. 5월 6-9일까지 나흘간 미국 플로리다주 올랜도에서 개최된 ‘SAS 이노베이트 2025(SAS Innovate 2025)’는
Model governance has moved from "nice to have" to a "non-negotiable". As organizations deploy AI across industries like health care, banking and government, the demand for transparency, trust and accountability is louder than ever. SAS experts Briana Ullman, Product Marketing Manager and Vrushali Sawant, Data Scientist, discussed what that looks
SAS' Enhanced Support model is structured into five progressive levels, ranging from Limited Support—designed for outdated software versions—to Premium Support, which offers the highest service standards, including enhanced SLAs, 24/7 assistance, and direct access to product experts. In particular, the combination of Extended Technical Support and Premium Support has proven to be a winning strategy for many companies undergoing modernization. This approach allows continued support for legacy environments during the migration to newer versions, minimizing operational risks and ensuring service continuity.
There’s nothing like the energy of a first-time experience – especially at SAS Innovate. Whether it was the keynotes, the tech demos, the chance to connect with peers, or just soaking it all in, first-time attendees had plenty to say about what made the event stand out. We caught up with
Using SAS Viya Workbench for efficient setup and execution, this beginner-friendly guide shows how Scikit-learn pipelines can streamline machine learning workflows and prevent common errors.
Accurately identifying lag structures between related time series is essential in public health forecasting, particularly during epidemics where delays between infections and hospitalizations affect planning. Using a simulated SEIR model and SAS Viya’s PROC TSSELECTLAG, distance correlation is shown to outperform Pearson correlation by correctly identifying nonlinear lag relationships—such as the true seven-day lag between new infections and hospital admissions.
If you think of SAS as a data, AI and analytics powerhouse, Epic Games as the studio behind Fortnite and Georgia-Pacific as the company that makes paper towels and more, you’re not wrong. But you’re also missing the bigger story. One that – quietly and collaboratively – is reshaping how
Call it what you want – an arms race, a land grab, a gold rush – but AI is now the centerpiece of most business strategies. Executives aren’t just curious about AI anymore; they are positioning their organizations for the technology's future. The problem? Most organizations aren’t ready. Even as
SAS announces continued support and releases for SAS 9 and a new role for SAS Enterprise Guide with SAS Viya.
No matter what industry you’re in or where you are in your career journey, you can benefit from AI. With that in mind, what can we all do to ensure that AI is more available and accessible to everyone? “The future is AI. It’s now. And it’s revolutionizing how we
Using 47 seasons of Survivor data, this analysis explores what gameplay traits correlate with winning, applying Python and SAS Viya Workbench to build predictive models. While stats like challenge wins and voting accuracy help narrow down potential winners, the findings suggest that intangible social dynamics play the most decisive role.
Introducing the new third edition of SAS For Dummies, covering SAS 9.4, SAS Viya, SAS Visual Analytics, SAS Viya Workbench and more!
