|SAS Enterprise Miner|
|Type||Private (Developed by SAS Institute)|
|Industry||Machine Learning Data Science Software|
|Founded||1976(SAS), 1999(SAS Enterprise Miner)|
|Slogan||Giving you The Power to Know®|
|Headquarters||Cary, North Carolina|
|Key people||Anthony James Barr, James H. Goodnight(CEO), John P. Sall|
|Investors||National Institutes of Health,|
|Number of employees||14,048|
|Related Certifications||Certificate in Machine Learning Industry Overview|
SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. SAS was developed at North Carolina State University from 1966 until 1976, when SAS Institute was incorporated. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.
SAS offers a flexible data preparation and management capabilities to build models with a rich, interactive visualization and data exploration. SAS also uses in-memory, in-database and grid capabilities for faster response and results.It offers state-of-the-art predictive analytics and data mining capabilities that enable organizations to analyze complex data, find useful insights and act confidently to make fact-based decisions. SAS Enterprise Miner is delivered as a distributed client/server system. Enterprise Miner's graphical interface enables users to logically move through the data mining process using the five-step SAS SEMMA approach: sampling, exploration, modification, modeling and assessment. This provides an optimized architecture so data miners and business analysts can work more quickly to create accurate predictive and descriptive models,and produce results that can be shared and incorporated into business processes. An easy-to-use, drag-and-drop interface is designed to appeal to analytic professionals. The advanced analytic algorithms are organized under core tasks that are performed in any successful data mining endeavor. R language code can be integrated inside of a SAS Enterprise Miner process flow diagram. This enables you to perform data transformation and exploration as well as training and scoring supervised and unsupervised models in R.
The major components of SAS Enterprise Miner are exploratory data analysis to visually explore data sets,model development and deployment,high performance data mining, credit scoring, analytics acceleration,scoring acceleration,model management and monitoring.
- 1972, State University faculty members Jim Goodnight and Jim Barr emerge as project leaders on a new USDA / NIH program called Statistical Analysis System.
- 1977: SAS named to Datamation Magazine's DataPro Software Honor Roll. It continued to appear on that list for the next three years.
- During the 1980s, SAS was one of Inc. Magazine's fastest growing companies in America from 1979 and 1985.
- November 11, 2011, SAS Institute announced the release of SAS Enterprise Miner 7.1.
- SAS Enterprise Miner was introduced in 1999.
- In 2011, the company released Enterprise Miner 7.1
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