Statistical analysis
SAS Visual Statistics
Discover, predict and act – decisively.
With SAS Visual Statistics, 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.
Key Features
Interactive data exploration and discovery combined with the ability to easily build and adjust huge numbers of predictive models on the fly.
Data access, preparation & quality
Access, profile, cleanse and transform data using an intuitive interface that provides self-service data preparation capabilities with embedded AI.
Custom chatbot creation
Create and deploy custom, natural language chatbots via an intuitive, low-code visual interface for chatbot-enabled insights and conversational user experiences.
Data visualization
Visually explore data, and create and share smart visualizations and interactive reports through a single, self-service interface. Augmented analytics and advanced capabilities accelerate insights and help you uncover stories hidden in your data.
Descriptive & predictive modeling
Explore and evaluate segments visually 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 & 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.
Cloud native
SAS Viya's architecture is compact, cloud native and fast. Whether you prefer to use the SAS Cloud or a public or private cloud provider, you'll be able to make the most of your cloud investment.
SAS Viya est une solution cloud-native et cloud-agnostic.
Consommez SAS comme vous l'entendez - SAS managed ou autogéré. Et où vous voulez.
Explore More on SAS Visual Statistics and Beyond
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Advanced analytics helps policymakers determine how new tax measures would affect citizensAscertaining the ‘winners’ and ‘losers’ of potential tax changes before regulations are implemented.
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Making prisons and communities safer with data visualizationIowa Department of Corrections uses SAS Viya on SAS Cloud to better manage supervised populations, make informed decisions and improve public safety.
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Predictive analytics and AI deliver a winning fan experience The Orlando Magic uses mobile app data and machine learning to personalize marketing campaigns and analyze game data.
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Analytics helps major public health system run efficient programs and improve patient careThe Los Angeles County Department of Health Services relies on advanced analytics from SAS to meet federal regulations, ensure financial viability and better serve a diverse population of more than 10 million people.
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Transforming the consumer banking experience through advanced analyticsCIMB Singapore uses SAS Viya to enhance business operations and keep pace with changing customer needs.
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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.
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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.
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Finland’s top retail bank applies AI to improve customer service and credit scoringS-Bank provides better customer service and faster, more accurate loan processing time using SAS Viya on Azure.
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Norway’s largest telecommunications, media and technology provider adapts to rapidly changing customer expectations using a hybrid cloud approachTelenor relies on SAS Viya on Azure and SAS Customer Intelligence 360 to provide fast, personalized customer service based on real-time analytics.
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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.
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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.
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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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Gartner positions SAS as a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms, Q1 2021Gartner positions SAS as a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms for the eighth consecutive year.
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It’s all in the research: Using AI to solve issues in health careWith the University of Alberta's new health data management and analysis platform, DARC, it can now increase research capacity and provide high-performance computing and data storage in a secure environment. SAS provided the university software to help make its platform thrive amidst a global pandemic.
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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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Artificial intelligence and IoT analytics keep aircraft operational for crucial missionsLockheed Martin revolutionizes aircraft maintenance with the SAS Platform.
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