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Find out what your peers are saying about Knime, IBM, Weka and others in Data Mining.
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 4 |
| Large Enterprise | 7 |
SAS Enterprise Miner enables comprehensive data management and analytics, handling extensive data volumes with diverse algorithms for model creation. Its integration and flexibility in SAS code usage make it suitable for both enterprise and personal use.
SAS Enterprise Miner is recognized for its data pipeline visualization, data processing, and statistical modeling capabilities. Its user-friendly GUI and automation support data mining tasks, decision tree creation, and clustering. However, improvements are needed in its interface visualization, affordability, technical support, and integration with languages like Python and cloud-native tech. Enhanced performance, visualization, and model development auditing, along with text analytics in the main license, are desirable upgrades. Integration with Microsoft SQL and combined offerings remains a priority.
What are SAS Enterprise Miner's most important features?SAS Enterprise Miner is applied across industries like banking, insurance, and healthcare for data mining, machine learning, and predictive analytics. It aids in activities such as text mining, fraud modeling, and forecasting model creation, handling structured and unstructured data, and performing ad hoc analysis to model business processes and analyze data clusters.
Teradata Aster® Analytics Portfolio provides a suite of ready-to-use, multi-genre advanced analytics functions that empowers business users to uncover and operationalize non-intuitive insights. Teradata Aster Analytics includes the Aster Database, Aster Client and the Aster Portfolio that consists of SQL, SQL-MapReduce and Graph functions for multi-genre advanced analytics. These functions provide everything from data acquisition and preparation to analytic modeling and visualization.
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