Interactive data exploration and discovery combined with the ability to easily build and adjust huge numbers of predictive models on the fly.
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 or Cloud Foundry platform as a service (PaaS).
Multiple users can explore data, then interactively create and refine predictive models.
Uncover opportunities faster than your competitors.
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.
Put better models into action faster.
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.
Boost analytical productivity.
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.
Gain the freedom to experiment.
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.
Explore More on SAS® Visual Statistics and Beyond
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Customer Story
Cancer treatment enters a new era with artificial intelligenceAmsterdam UMC uses the SAS Platform and AI solutions to increase speed and accuracy of tumor evaluations.
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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.
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Boosting institutional research with data governance and self-service reportingThe University of Idaho invests in SAS to give administrators access to trusted, insight-rich data.
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A model of institutional research champions the value of analytics for allOklahoma State University uses SAS to create an analytics culture and increase student success.
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Zeroing in on property values with machine learningArtificial intelligence improves assessment accuracy and productivity in Wake County.
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University aces data strategy to retain more studentsBetter student outcomes, million-dollar savings just the beginning for the University of North Texas.
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Customer Story
Targeted offers give hockey fans the royal treatmentLA Kings extend hot streak off the ice with analytics-grounded customer intelligence.
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