Find the value in your data – big or small – and use it to your advantage. Now you can tackle your most complex challenges, and get precise answers – instantaneously. Only SAS combines industry-leading analytics with a powerful in-memory engine and an intuitive interface, so you can build predictive models faster than you ever imagined.
Get precise answers from diverse data.
Quickly surface insights hidden in vast stores of data. And discover and evaluate new opportunities. We've combined powerful, predictive analytics with visual data exploration capabilities in a single, interactive environment. The result? Business analysts and statisticians can do more with data than ever before.
Develop more models faster. With greater precision.
How long does it take to run your models? Hours? Our multicore processing environment knocks that down to minutes or seconds. So you can build models to target specific groups or segments. Run multiple scenarios simultaneously. Ask more what-if questions. All using data volumes never before possible.
Make data scientists and statisticians more productive.
Stay agile in a big data world, thanks to in-memory processing. Multiple users can customize models – by adding or changing variables, removing outliers, etc. – and quickly see how those changes affect model outcomes. You get greater productivity from your analytic talent, and greater value from your analytics.
Uncover insights hidden in your data. Faster than ever.
Enterprise data is always in flux, so you need an analytics solution that responds quickly to new requirements. SAS Visual Statistics uses an in-memory engine to perform complex analytic computations, without copying or caching data. Now you can test new ideas. Refine models on the fly. And get answers faster.
- 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.