Products & Solutions / Model Development & Deployment

SAS® Enterprise MinerTM

Using data mining to unearth valuable insights for better decisions with less time and effort

SAS Enterprise Miner streamlines the data mining process to create highly accurate predictive and descriptive models based on analysis of vast amounts of data from across the enterprise. Forward-thinking organizations today are using SAS data mining software to detect fraud, anticipate resource demands, increase acquisitions and curb customer attrition.

Benefits

  • Support the entire data mining process with a broad set of capabilities.
  • Build better models with a versatile data mining workbench.
  • Enable business analysts to quickly and easily derive insights in a self-sufficient and automated manner.
  • Enhance accuracy of predictions and easily share reliable information to improve the quality of decisions.
  • Ease the model deployment and scoring process.

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Features

  • Powerful, easy-to-use GUI, as well as batch processing for large jobs
  • Data preparation, summarization and exploration
  • Advanced predictive and descriptive modeling
  • Fast, easy and self-sufficient way for business users to generate models
  • Business-based model comparisons, reporting and management
  • Automated scoring process
  • Open, extensible design
  • Scalable processing

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" Our profitability around marketing interventions programs is much higher because of the precision of understanding that SAS provides."

—David Norton

Chief Marketing Officer

Harrah's Entertainment

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Product Demo

SAS Enterprise Miner streamlines data mining to create accurate predictive and descriptive models based on large volumes of enterprisewide data.


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How SAS® Is Different

  • Integrated data access, data preparation and management capabilities. Data access, management and cleansing are seamlessly integrated, making it easier to prepare data for analysis. SAS Enterprise Miner also uses push-down integration with third-party databases. Robust variable selection and data modification tools improve the quality of your data, which leads to better modeling and more reliable results.
  • Interactive visualization and data exploration. A rich, interactive environment that is optimized for data discovery, visual exploration and understanding relationships is provided in a point-and-click environment with dynamically linked tables and graphics. The JMP® Pro client provides an ideal environment for data discovery and model assessment.
  • Extensive breadth and depth of analytics and numerous ways to develop models and approaches. SAS Enterprise Miner provides the most comprehensive set of advanced predictive and descriptive modeling algorithms, including market basket analysis, decision trees, gradient boosting, bootstrap forest, least angular regression splines, neural networks, linear and logistic regression, partial least squares regression, survival analysis, time series data mining, incremental response/net lift models and many more. Also included are industry-specific models for customer issues such as credit scoring and ratemaking for insurance.
  • An exclusive step-by-step approach for faster results. Our advanced analytic algorithms are organized under the core tasks that are performed in any successful data mining endeavor: sampling, exploration, modification, modeling and assessment (SEMMA). In each step, you perform an array of actions as the data mining project develops. Scoring code is delivered in SAS, C, Java and PMML for scoring in batch and real time in the SAS environment and others.
  • Special applications for business analysts and in-depth capabilities for modelers and data miners. Business analysts and subject-matter experts can quickly generate predictive models using the SAS Rapid Predictive Modeler task in SAS® Enterprise Guide® or the SAS Add-In for Microsoft Office (Microsoft Excel only), while statisticians, modelers and data miners can tweak details and embed their own algorithms into their model flows.
  • Ability to deliver scale and speed required for big data. SAS has taken the industry lead in offering a range of options (grid computing, in-database processing and in-memory analytics) for high-performance analytic deployments. A select set of procedures and nodes from SAS Enterprise Miner have been enabled to run in a distributed, in-memory environment (SAS High-Performance Analytics Server, which is licensed separately). This product lets customers develop models with hundreds or thousands of variables, and run the models in minutes or seconds.
  • A Windows desktop version, SAS Enterprise Miner for Desktop, is also available. It is designed for quantitative analysts in small to midsized firms, or those who work independently in departments faced with solving critical business issues or complex research problems.

Benefits

  • Support the entire data mining process with a broad set of capabilities. Regardless of your data mining preference or skill level, SAS provides flexible software that addresses complex problems. Going from raw data to accurate, business-driven data mining models becomes a seamless process, enabling the statistical modeling group, business managers and the IT department to collaborate more efficiently.
  • Build better models with a versatile data mining workbench. SAS Enterprise Miner includes an interactive self-documenting process flow diagram environment that dramatically shortens model development time for statisticians and data miners. It efficiently maps the entire data mining process to produce the best possible results.
  • Enable business analysts to quickly and easily derive insights in a self-sufficient and automated manner. The SAS Rapid Predictive Modeler task running from SAS® Enterprise Guide® or the SAS Add-In for Microsoft Office (Excel only) enables business users and subject-matter experts with limited statistical skills to automatically generate predictive models for common business scenarios and act on them quickly and effectively. Analytic results can be consumed in simple and easy-to-understand charts to derive the insights needed for better decision making.
  • Enhance accuracy of predictions and easily share reliable information to improve the quality of decisions. Better-performing models with modern, innovative algorithms and industry-specific methods  enhance the stability and accuracy of predictions, which can be verified easily by visual model assessment and validation metrics. Both analytical and business users enjoy a common, easy-to-interpret visual view of the data mining process. Predictive results and assessment statistics from models built with different approaches can be displayed side-by-side for easy comparison. The resulting diagrams serve as self-documenting templates that can be updated easily or applied to new problems without starting over. In addition, model profiling provides an understanding of how the predictor variables contribute to the outcome being modeled.
  • Ease the model deployment and scoring process. Scoring – the process of applying a model to new data – is the end result of many data mining endeavors. SAS Enterprise Miner automates the tedious scoring process and supplies complete scoring code for all stages of model development in SAS, C, Java and PMML languages. The scoring code can be deployed in a variety of real-time or batch environments within SAS, on the Web or directly into relational databases, or embedded in business processes. These capabilities can save you time, enable more accurate results and help you make decisions that add the greatest value.

Features

Powerful, easy-to-use GUI, as well as batch processing for large jobs
  • Interactive GUI for building process flow diagrams.
  • Batch processing code for scheduling large modeling and scoring jobs.
Data preparation, summarization and exploration
  • Access and integrate structured and unstructured data sources.
  • Outlier filtering.
  • Data sampling.
  • Data partitioning.
  • File import.
  • Integration with R (from within JMP® Pro) to extend the types and comparison of models.
  • Merge and append tools.
  • Univariate statistics and plots.
  • Bivariate statistics and plots.
  • Batch and interactive plots.
  • Segment profile plots.
  • Easy-to-use Graphics Explorer wizard and Graph Explore node.
  • Interactively linked plots and tables.
  • Interactive Graph Builder enables you to drag and drop variables into the template to construct graphs for understanding relationships.
  • Data transformations.
  • Time series data preparation and analysis.
  • Interactive variable binning.
  • Rules Builder node for creating ad hoc data-driven rules and policies.
  • Data replacement.
Advanced predictive and descriptive modeling
  • Clustering and self-organizing maps.
  • Market basket analysis.
  • Sequence and Web path analysis.
  • Dimension reduction techniques:
    • Variable selection.
    • LARS (Least Angle Regression) variable selection.
    • Principal components.
    • Variable clustering.
    • Time series mining.
  • Linear and logistic regression.
  • Decision trees.
  • Gradient boosting.
  • Neural networks.
  • Support Vector Machine (experimental).
  • Partial least squares regression.
  • Two-stage modeling.
  • Memory-based reasoning.
  • Model ensembles, including bagging and boosting.
  • Time series data mining.
  • Survival analysis.
  • Ratemaking for insurance.
  • Incremental response/net lift models.
Fast, easy and self-sufficient way for business users to generate models
  • SAS Rapid Predictive Modeler automatically generates predictive models for a variety of business problems.
  • Business analysts and subject-matter experts work from SAS® Enterprise Guide® or the SAS Add-In for Microsoft Office (Excel only).
  • Models can be opened, augmented and modified in SAS® Enterprise Miner TM .
  • Produces concise reports, including variable importance charts, lift charts, ROC charts and model scorecards, for easy consumption and review.
  • Ability to score the training data with an option to save the scored data set.
Business-based model comparisons, reporting and management
  • Assessment features for comparing multiple models using lift curves, statistical diagnostics and ROI metrics.
  • Highly visual model comparison interface.
  • Innovative Cutoff node examines to determine probability cutoff point(s) for binary targets.
  • Report creation and distribution.
  • Model result packages.
  • Group processing for multiple targets and segments.
  • A profiler provides an interactive environment for comparing and contrasting competing models and assessing the importance of key input variables on the predicted response times.
  • Macro for registering models developed with SAS code into the SAS Metadata Server.
Automated scoring process
  • Interactive scoring in a variety of real-time or batch environments.
  • Automatically generates score code in SAS, C, Java and PMML.
  • Score data based on models saved as PMML documents (experimental).
  • Score SAS Enterprise Miner models directly inside Aster, EMC Greenplum, IBM DB2, IBM Netezza, Oracle and Teradata databases with SAS Scoring Accelerator.
  • Model registration and management.
  • Deploy models in multiple environments.
  • Integrate SAS Enterprise Miner training and scoring processes directly into other SAS solutions.
Open, extensible design
  • Extension node for easily adding tools and personalized SAS code.
  • Interactive editor features for training and score code.
  • Integrate text mining for analysis of both structured and unstructured data.
  • Incorporate time series, Web paths and associations rules as additional input variables into the model development process.
Scalable processing
  • The Java client and the SAS server architecture both scale from single-user to large enterprise solutions.
  • Server-based processing and storage.
  • In-database and in-memory processing options.
  • Asynchronous model building.
  • Ability to stop processing cleanly.
  • Grid computing.
  • Parallel processing.
  • Multithreaded predictive algorithms.

Demos

Demo
SAS® Rapid Predictive Modeler demo

Learn how to build predictive models very quickly using the SAS Rapid Predictive Modeler component of SAS® Enterprise Miner™.

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Demo
SAS Enterprise Miner software demo

SAS Enterprise Miner streamlines data mining to create accurate predictive and descriptive models based on large volumes of enterprisewide data.

View Demo

Screenshots

Screenshot
Quickly and automatically generate predictive models from familiar, user-friendly interfaces.

With SAS Rapid Predictive Modeler, business analysts and subject-matter experts can rapidly explore and analyze their data using either the familiar, visual interfaces available in Microsoft Excel or the guided analysis capabilities of SAS Enterprise Guide. In addition, data mining specialists and statisticians can generate quick, baseline models when they are short on time and resources.

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Filter extreme values interactively with the Filter node.

The shaded region defines the variable range to keep.

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Easily explore your data using interactive features.

Interactive graphs are automatically saved within the results of the Graphics Explore node.

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Develop decision trees interactively or in batch.

Numerous assessment plots to help gauge overall tree stability are included.

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Segment your data using clustering or self-organizing maps.

Segment your data using clustering or self-organizing maps. Visualizations are also provided to help determine which variables are important in distinguishing cluster membership as well as profile plots showing the distribution of the inputs and other factors in each cluster.

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Evaluate multiple models together.

The Model Comparison node provides an easy-to-use framework for comparing models to determine the best one.

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System Requirements

Host Platforms/Server Tier
  • HP/UX on Itanium: 11iv3 (11.31)
  • IBM AIX R64 on POWER architecture 7.1
  • IBM z/OS: V1R11 and higher
  • Linux x64 (64-bit): Novell SuSE 11 SP1; Red Hat Enterprise Linux 6.1; Oracle Linux 6.1
  • Microsoft Windows on x64 (64-bit):
    Desktop: Windows 7* x64 SP1; Windows 8** x64
    Server: Windows Server 2008 x64 SP2 Family; Windows Server 2008 R2 SP1 Family; Windows Server 2012 Family
  • Solaris on SPARC: Version 10 Update 9
  • Solaris on x64 (x64-86): Version 10 Update 9; Version 11
Client Tier
  • Microsoft Windows (64-bit): Windows 7* x64 SP1; Windows 8** x64
Required software
  • Base SAS®
  • SAS/STAT®
  • SAS Rapid Predictive Modeler requires SAS Enterprise Miner to produce predictive models. The SAS Rapid Predictive Modeler task is available from either SAS Enterprise Guide or SAS Add-In for Microsoft Office (Microsoft Excel only).
JMP® Pro Now Included
  • JMP Pro is included with SAS Enterprise Miner 6.2 (SAS 9.2 release) and SAS Enterprise Miner 7.1 (SAS 9.3 release). It runs only on 32-bit or 64-bit versions of Windows XP Professional, Windows Server 2003, Windows Server 2008, Windows Vista (except Vista Home Basic edition) and Windows 7 (except Starter and Home Basic editions).

* NOTE: Windows 7 supported editions are: Professional, Ultimate and Enterprise.
** NOTE: Supported editions include: Windows 8, Windows 8 Pro, Windows 8 Enterprise.

Ready to learn more?

Call us at 1-800-727-0025 (US and Canada) or request more information.