Products & Solutions / DATA MINING

Data mining with SAS® Enterprise MinerTM

Unearthing valuable insight - profitable data mining results 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, minimize credit risk, anticipate resource demands, increase response rates for marketing campaigns and curb customer attrition.

Benefits

  • Support the entire data mining process with a broad set of tools.
  • Build more models faster with an easy-to-use GUI.
  • Enhance accuracy of predictions and easily share reliable information to improve the quality of decisions.
  • Ease the model deployment and scoring process.

Read more

Features

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

Read more

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

—David Norton

Senior Vice President of Relationship Marketing

Harrah's Entertainment

Read full story

Screenshots

SAS Enterprise Miner software's easy-to-use GUI for data mining.

Screenshot: SAS Enterprise Miner software's easy-to-use GUI for data mining.
More ScreenshotsEnlarge
 

How SAS® Is Different

  • Data access, management and cleansing are seamlessly integrated, making it easier to prepare data for analysis.
  • Robust variable selection and data modification tools improve the quality of your data, which leads to better modeling and more reliable results.
  • With multithreaded algorithms and support for multiprocessing and grid computing, execution time is reduced and hardware resources are used more efficiently.
  • Smart defaults allow business users to produce models quickly, while advanced statisticians can tweak details and embed their own algorithms into their model flows.
  • The rich Java client interface enables fast, maintenance-free distribution throughout large organizations, and data mining projects can be shared among analysts across different units and regions.
  • 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.
  • SAS Enterprise Miner provides the most comprehensive set of advanced predictive and descriptive modeling algorithms, including market basket analysis, decision trees, gradient boosting, least angular regression splines, neural networks, linear and logistic regression, partial least squares regression and many more.
  • Scoring code is delivered in SAS, C, Java and PMML for scoring in batch and real-time in both SAS and non-SAS environments.

A Windows desktop version, SAS Enterprise Miner for Desktop, is also available. It is designed for quantitative analysts in small to medium-sized 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 tools. 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 more models faster with an easy-to-use GUI. SAS Enterprise Miner’s process flow diagram environment dramatically shortens model development time for both business analysts and statisticians. SAS Enterprise Miner 6.1 includes an intuitive user interface that incorporates common design principles established for SAS software, as well as additional navigation tools. The process flow diagram provides a complete audit trail of the analyses, and along with user-defined notes and model result packages, is useful for version control. The GUI can be tailored for all analysts' needs via flexible, interactive property sheets, code editors and display settings.
  • Enhance accuracy of predictions and easily share reliable information to improve the quality of decisions. Better-performing models with new innovative algorithms 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.
  • 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. The scoring code can be deployed in a variety of real-time or batch environments within SAS, on the Web or directly in relational databases. The outcome is faster implementation of data mining results.

Features

Powerful, easy-to-use GUI, as well as batch processing for large jobs
  • Interactive GUI for building process flow diagrams.
  • Batch processing code or scheduling large modeling and scoring jobs.
Scalable processing
  • Java client/SAS server architecture scales from single-user to large enterprise solutions.
  • Server-based processing and storage.
  • Asynchronous model building.
  • Ability to stop processing cleanly.
  • Grid computing.
  • Parallel processing.
  • Multithreaded predictive algorithms.
Data preparation, summarization and exploration
  • Access to more than 50 file structures.
  • Outlier filtering.
  • Data sampling.
  • Data partitioning.
  • File import.
  • 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 Graphics Explore node.
  • Interactively linked plots and tables.
  • 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.
    • Manage time metrics with descriptive data.
  • Linear and logistic regression.
  • Decision trees.
  • Gradient boosting.
  • Neural networks.
  • Partial least squares regression.
  • Two-stage modeling.
  • Memory-based reasoning.
  • Model ensembles, including bagging and boosting.
Business-based model comparisons, reporting and management
  • Assessment features for comparing multiple models using lift curves, statistical diagnostics and ROI metrics.
  • Highly visual model comparision 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.
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 SAS Enterprise Miner models directly inside the Teradata database with SAS Scoring Accelerator for Teradata.
  • Model registration and viewing.
  • Deploy models in multiple environments.
  • Integrate SAS Enterprise Miner training and scoring processed 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 times series, Web paths and associations rules as additional input variables into the model development process.

Screenshots

SAS Enterprise Miner software's easy-to-use GUI for data mining.

Build more models faster with SAS Enterprise Miner software's easy-to-use GUI for data mining.

Enlarge

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.

Enlarge

System Requirements

Client environment

  • Linux for x86 (x86-32): RHEL 4 and 5, SuSE SLES 9 and 10
  • Microsoft Windows (x86-32): Windows XP Professional, Windows Server 2003, Windows Vista*
  • Microsoft Windows on x64 (EM64T/AMD64): Windows XP Professional for x64, Windows Vista* for x64, Windows Server 2003 for x64
  • Solaris on SPARC: Version 9, 10
  • Solaris on x64: Version 10

*   NOTE:  Windows Vista Editions that are supported include Enterprise, Business and Ultimate.

Server environment

  • AIX: Release Version 5.3 and Version 6.1 on POWER architectures
  • HP-UX PA-RISC: HP-UX 11iv2 (11.23), 11iv3 (11.31)
  • HP-UX Itanium: HP-UX 11iv2 (11.23), 11iv3 (11.31)
  • Linux for x86 (x86-32): RHEL 4 and 5, SuSE SLES 9 and 10
  • Linux for x64 (EM64T/AMD64):  RHEL 4 and 5, SuSE SLES 9 and 10
  • Microsoft Windows (x86-32): Windows XP Professional, Windows Server 2003, Windows Vista*
  • Microsoft Windows on x64 (EM64T/AMD64): Windows XP Professional for x64, Windows Vista* for x64, Windows Server 2003 for x64
  • Microsoft Windows (on Itanium): Windows Server 2003
  • Solaris on SPARC: Version 9, 10
  • Solaris on x64: Version 10

*   NOTE:  Windows Vista Editions that are supported include Enterprise, Business and Ultimate.

Required software

  • Base SAS
  • SAS/STAT®

Note: These are the technical requirements for SAS Enterprise Miner 6.1.

 

Ready to learn more?

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