SAS Visual Statistics clustering screenshot on desktop monitor

SAS® Visual Statistics

Predictive analytics. Redefined.

Find the value in your data – big or small – and use it to your advantage. Tackle your most complex challenges, and get precise answers – instantly. Only SAS combines industry-leading analytics with a powerful in-memory engine, so you can build and refine predictive models faster than you ever imagined.


Beat competitors with precise insights.

Discover and evaluate new opportunities from every possible angle. We've combined powerful, predictive analytics with visual data exploration in a single, interactive environment. The result? You can find insights that competitors miss, and act decisively.

Boost staff productivity.

Multiple users can fine-tune models interactively. Add variables. Remove outliers. And instantly see the effect on model outcomes. Which model has the most predictive power? It’s easy to find out – and get more value from your big data and your staff.

Develop and run more models faster.

How long does it take to run your models? Hours? In-memory processing reduces that to minutes. Build numerous models to target specific groups or segments simultaneously. Ask more what-if questions. And get better, faster answers.

Stay agile with in-memory computing.

Perform complex analytic computations using an in-memory engine. Modelers can quickly test new ideas, try different modeling techniques and refine models on the fly to produce the best results – using data volumes never before possible.

Demos & Screenshots


SAS Visual Statistics Logistic Regression Screenshot on Laptop
  • Data visualization and exploration. Quickly identify predictive drivers among thousands of explanatory variables, and interactively discover outliers and data discrepancies through integration with SAS Visual Analytics.
  • Descriptive modeling. Visually explore and evaluate segments for further analysis using k-means clustering.
  • Predictive modeling. Build predictive models using techniques like linear regression, generalized linear modeling, logistic regression and classification trees.
  • Dynamic group-by processing. Concurrently build models and process results for each group or segment without having to sort or index data each time.

  • In-memory analytical processing. Build models faster. There's no need to write data to disk or perform data shuffling, and you can instantly see the impact of changes (e.g., adding new variables or removing outliers).
  • Model comparison and assessment. Generate model comparisons, including lift charts and ROC charts for one or more models.
  • Model scoring. Generate SAS DATA step code, and apply it to new data.
  • Platform support. Supports Hadoop distributed file system (Cloudera or Hortonworks distributions), as well as Teradata and Pivotal databases.

Technical Information

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