Descriptive and predictive modeling
Visually explore and evaluate segments for further analysis using k-means clustering, scatter plots and detailed summary statistics. Use machine learning techniques to build predictive models from a visual or programming interface.
Open, code-based model development
Programmatically access analytical actions from SAS Studio, call them from other languages – Python, R, Lua, Java – or use public REST APIs to add SAS Analytics to existing applications.
Dynamic group-by processing
Concurrently build models and process results for each group or segment without having to sort or index data each time.
Model comparison, assessment and scoring
Generate model comparison summaries (lift charts, ROC charts, concordance statistics, misclassification tables) on one or more models. Export models as SAS DATA step code, and apply them to new data.
Distributed, in-memory analytical processing
Uses in-memory analytical processing to provide answers to a range of business questions in a single, scalable and governed environment.
Flexible deployment options
Runs on commodity hardware, in a private or public cloud infrastructure, Cloud Foundry platform as a service (PaaS) or managed software as a service (SaaS).
Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue.
Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with automatically generated score code.
Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly.
Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets – whether created using SAS or other languages like R, Python, Java or Lua – within a common solution.
Customer Story
Shaping higher education through cloud analyticsGeorge Mason University relies on SAS Viya to uncover insights to improve operational effectiveness and increase student success.
White Paper
Redefine Your Analytics Journey With Interactive Data Exploration and Predictive AnalyticsWhat if your analytics journey were easier? It can be, in five easy steps. Learn how SAS Visual Analytics and SAS Visual Statistics together can provide a fast, fun way to explore data, build models and find the best performer.
Article
Stopping the Zika virus: The potential of big data, analyticsHow do you stop global outbreaks? The answer may be in the data about the disease and how it spreads.
Customer Story
Finding the next football star with artificial intelligenceDutch sports analytics company SciSports uses emerging tech to innovate on the pitch.
White Paper
Redefine Your Analytics Journey With Interactive Data Exploration and Predictive AnalyticsWhat if your analytics journey were easier? It can be, in five easy steps. Learn how SAS Visual Analytics and SAS Visual Statistics together can provide a fast, fun way to explore data, build models and find the best performer.
E-Book
How Any Size Organization Can Supersize Results With Data VisualizationEveryone makes better decisions with easy access to powerful, interactive analytics – no matter the size of the business. This e-book profiles six organizations that are using self-service data visualization and exploration to make big improvements in the way they work.
White Paper
Using Analytics With Open Data to Build a Stronger GovernmentLearn how governments can use open data and SAS to pinpoint, analyze, solve and predict problems and uncover new opportunities.
Conclusion Paper
The Use of Open Source is Growing. So Why Do Organizations Still Turn to SAS?This conclusions paper summarizes a session at the 2014 Hadoop Summit presented by Brian Garrett, Principal Solutions Architect at SAS Institute Inc. titled, “With the Rise of Open Source, Why Organizations Still Turn to SAS.” In it, he explains why corporate analytics requirements are best served when companies run both SAS enterprise-class analytics solutions and open source solutions together. Garrett explains how these technologies meet different needs and co-exist well. He also highlights recent SAS software enhancements that allow analysts to incorporate R algorithms into analytic processes as part of a comprehensive, enterprise-class SAS analytics platform.
White Paper
Using Next-Generation Advanced Analytics to Harness Big DataDiscover why Heavy Reading recommends using advanced analytics from proven vendors to obtain real-time intelligence from all your big data.
Conclusion Paper
Fast and Furious: Big Data Analytics Meets HadoopConclusions paper from a presentation at the 2014 Strata Santa Clara big data conference, in which two SAS data experts demonstrated new ways of gaining insights from big data at speeds that will redefine how organizations solve complex problems
Conclusion Paper
Big Data, Analytics and HadoopSAS and Hadoop are natural partners. Hadoop provides distributed storage and processing power. SAS treats Hadoop as just another data source and complements it with data management, data discovery and advanced analytics. This conclusions paper highlights two ways you can work with Hadoop data from within a familiar and interactive SAS Analytics environment – either with the graphical user interface of SAS® Visual Statistics or streamlined programming via SAS In-Memory Statistics for Hadoop.
Customer Story
Zeroing in on property values with machine learningArtificial intelligence improves assessment accuracy and productivity in Wake County.
Customer Story
Machine learning helps personalize the gift card experience across retail channelsEpipoli uses SAS artificial intelligence and customer intelligence solutions to craft relevant, real-time offers for customers.
Customer Story
Better customer service via machine learningAdvanced analytics helps Rogers Communications become more customer-centric, cutting customer complaints in half.
Customer Story
Finding the next football star with artificial intelligenceDutch sports analytics company SciSports uses emerging tech to innovate on the pitch.
Customer Story
Shaping higher education through cloud analyticsGeorge Mason University relies on SAS Viya to uncover insights to improve operational effectiveness and increase student success.
Interview
Data visualization: A wise investment in your big data futureData visualization technologies can help the practice of data-driven decision making really take hold. But putting data visualization software in the hands of business users? Is it crazy – or crazy smart?
Interview
The University of Alabama makes better decisions through education analyticsAt the University of Alabama, the Office of Institutional Research and Assessments use analytics and data visualizations to uncover better student outcomes.
Article
Stopping the Zika virus: The potential of big data, analyticsHow do you stop global outbreaks? The answer may be in the data about the disease and how it spreads.
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