Team Name Team CLMers Track Public Sector Use Case *Our team, CLMers, proposes an AI-powered wildfire prevention platform that helps public authorities anticipate and mitigate wildfires before they occur. The solution combines weather forecasts, satellite imagery, vegetation indicators, historical wildfire records, and open data to generate dynamic wildfire risk assessments.  Using predictive analytics and geospatial intelligence, the platform estimates ignition risk, fire spread potential, and expected impact. It also provides decision support recommendations to help optimize prevention measures and resource allocation.  By shifting wildfire management from reaction to prevention, the project helps protect ecosystems, rural communities, and critical infrastructure while improving climate resilience and public-sector efficiency.  Built on scalable cloud technologies and open data, the solution can be replicated in any wildfire-prone region worldwide.  Vision: From firefighting to fire prevention. Technology SAS Viya Region Spain Team lead Cobas López, Christian Team members 18 Team members Social media handles *all team members' social media links here* Is your team interested in participating in an interview? Y Optional: Expand on your technology expertise     The Team     Pitch Jury ... View more

Team Name Ludlowe Legacy Track  Track: Health care & Life Sciences Use Case GreenSeer is an auto-ML-inspired environmental intelligence platform designed to help policymakers and organizations more efficiently evaluate the effectiveness of environmental policies and pollution-control interventions. By combining decades of EPA pollution data, policy documents, and external factors such as weather, GreenSeer uses intelligent model selection, statistical analysis, and explainable AI to identify meaningful patterns and assess environmental changes. The results are presented through an interactive SAS-powered dashboard that translates complex analyses into clear, actionable insights for better environmental decision-making. Technology SAS Viya, Python, Forecasting Models, Causal Inference; EPA air-quality and emissions data, NOAA weather and smoke data, transportation and energy datasets, and more. Region Raleigh, NC, Fairfield, CT Team lead Andrew Kutsch Team members @andyk08   Andrew Kutsch, Adil Syed, Gamid Muratbekov Social media handles *all team members' social media links here* Is your team interested in participating in an interview? Y Optional: Expand on your technology expertise     ... View more

Part of our #SASVoice | Learning from Our Customers series, sharing practical lessons from real customer situations.   The Challenge A global organization was introducing new technologies, modernizing business processes and driving transformation across multiple areas of the business.   This raised an important question: Did employees have the skills needed to turn these investments into business value?   The challenge was not simply providing more training. It was understanding where capability gaps existed and connecting workforce development with the organization's broader business priorities.   Without this connection, learning risked becoming a separate activity rather than a practical part of the transformation strategy.   The Approach The organization took a more structured approach to understanding and developing workforce capabilities.   Skills assessments helped identify capability gaps. Development planning and role-based learning opportunities then helped connect those needs with relevant development pathways.   Learning priorities were aligned more closely with business and transformation priorities, moving the conversation beyond course completion and towards longer-term capability building.   The Outcomes The approach created a clearer connection between workforce development and broader transformation priorities.   It was designed to support: Better alignment between learning investments and business goals Improved workforce preparedness Stronger support for transformation initiatives Greater focus on long-term capability development     Lessons Learned Learning creates the greatest value when there is a clear reason for it. Before asking: “Which course should people take?” organizations may benefit from first asking: “Which capabilities do we need, where are the gaps and what business objective are we trying to support?” Starting with the need rather than the course can help create learning pathways that are more relevant to employees and more closely connected with business priorities.   Learn More Not sure where the most important skills gaps are in your organization? A Learning Needs Assessment can help identify priorities before defining the right learning approach. SAS Premium Learning Subscription can then support ongoing, role-based skills development across teams and learning needs. ➡️ Learn more about SAS Premium Learning Subscription: https://www.sas.com/gms/redirect.jsp?detail=PLN69124_1174760520   Editor's Note: This article is based on real customer experiences. Specific customer details have been anonymized to focus on the business challenge, approach and lessons learned.      ... View more

You open a new business evolution plan, click the Variable 1 column, and the variable you need isn't in the list. You know it's in your data. You can see it in the portfolio. Still, SAS Asset and Liability Management acts like it has never heard of it.   The solution is doing exactly what it's told. Before a variable can show up in a business evolution plan or an allocation scheme, someone has to tell the data definition what job that variable is allowed to do.   The purpose of this post is to explain what segmentation, target and allocation variables are, where each one lives, and how to switch them on so they appear in your business evolution plans and allocation schemes. ... View more

When viewing a SAS Visual Analytics report, do you ever find yourself having to select the same prompt values, actions, sorts, drill-downs, filters, ranks, etc.? All of these things are saved in the report state. You might be interested in saving each report state, so you can easily reapply it later. Using the Reports API, a SAS Viya Job and the web content object, I created a report state selector that you can use to save and reapply report states to your report. In this post, I outline why and how you would use this. ... View more