SAS Enterprise Miner Reviews

SAS Enterprise Miner is perceived as a highly expensive solution with complex licensing models, including annual renewals at approximately 35% of the initial cost. Users highlight the necessity of purchasing licenses for each component, which increases overall expense. While costly for individuals, enterprises may find value in bulk licenses. Users suggest improvements in licensing flexibility to better access functionalities. Alternative solutions like R, particularly Microsoft R, are often considered for their cost-effectiveness and flexibility.

• "The solution must improve its licensing models."
• "The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
• "This solution is for large corporations because not everybody can afford it."

SAS Enterprise Miner is primarily utilized for tasks such as data mining, machine learning, modeling, and predictive analytics. Users employ it for text mining, business processes, forecasting models, and data management. It is applied across various domains including banking, insurance, and healthcare for purposes like ad hoc analysis, client consolidation, structured and unstructured data mining, and fraud modeling techniques. Users often focus on the analytical tools section for clustering and classification.

SAS Enterprise Miner is scalable, though performance may decline with raw data over 50GB. Costs rise with scaling, and some require multi-socket server licensing. Users appreciate its scalability, but costs and organization size may affect opinions. Users generally report no issues scaling, with varying needs and usage patterns within organizations. The tool helps scale analytical projects, and its scalability is rated favorably, though knowledge and experience levels differ among users.

SAS Enterprise Miner is noted for strong stability, particularly version 14.3. Users find it stable and reliable, without major glitches or crashes. Compatibility issues with Java can arise, requiring monthly system restarts. Some report variances in accuracy, impacting AI forecasting. It's praised for flexibility in parameters compared to other professional programs. Stability can be machine-dependent, especially with low RAM handling extensive data. Most users do not encounter significant stability challenges and rate it highly.