- Visual data exploration and discovery. Use SAS Visual Analytics to easily identify predictive drivers among multiple exploratory variables, and visually identify outliers and data discrepancies.
- Descriptive modeling. Visually explore and evaluate segments for further analysis using k-means clustering, scatter plots and detailed summary statistics.
- Predictive modeling. Build predictive models using techniques like linear regression, logistic regression, generalized linear models and decision trees – with point-and-click ease.
- Model comparison and assessment. Generate model comparison summaries (lift charts, ROC charts, concordance statistics, misclassification tables) on one or more 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. You can also access SAS analytical algorithms from other environments using the programming language you prefer – Python, Java, R or Lua.
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