Find the value in your data, no matter the size. Multiple users can explore and visualize data, then interactively create and refine descriptive and predictive models. Distributed, in-memory processing slashes model development time so you can run complex analytic computations – and get precise results – in minutes.
Beat the competition with savvy insights.
Quickly surface insights hidden in vast data stores. Discover and evaluate new opportunities your competitors will miss. Find new ways to grow revenue. Because SAS Visual Analytics is included with the solution, business analysts and statisticians can use powerful, predictive analytics and visual data exploration capabilities to do more with data than ever before.
Boost your analytical teams' productivity.
Multiple users can quickly and interactively customize models – adding or changing variables, removing outliers, etc. – and instantaneously see how those changes affect model outcomes. Which model provides the most predictive power? It’s now easy to find out – and get more value from your big data analytics.
Run more models faster – with precision.
Our multicore processing environment reduces that to minutes. You can build models to target specific groups or segments, and run numerous scenarios simultaneously. Ask more what-if questions, and get fast answers. Refined models produce better results.
Stay agile with in-memory computing.
Perform complex analytic computations fast 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
- An interactive data exploration and modeling environment. Quickly identify predictive drivers and interactively discover outliers across multiple variables with SAS Visual Analytics. Then create powerful descriptive and predictive models with a simple drag-and-drop interface.
- 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 such as 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 on diverse data sets, including Hadoop. There's no need to shuffle data or write data to disk, and you can instantly see the impact of changes (e.g., adding new variables or removing outliers).
- Model comparison and assessment. Generate model comparison summaries (e.g., lift charts, ROC charts, concordance statistics and misclassification tables) on one or more models.
- Model scoring. Generate SAS DATA step code, and apply it to new data.
- SAS Visual Analytics included for data visualization and reporting. Design and distribute BI reports and dashboards, explore relevant data through interactive data visualization, and provide easy-to-use, self-service analytics to more users.
- Platform support. Supports Hadoop distributed file system (Cloudera or Hortonworks distributions), as well as Teradata, Greenplum (Pivotal), SAP HANA and Oracle databases.