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.
| Product | Mindshare (%) |
|---|---|
| SAS Enterprise Miner | 7.5% |
| IBM SPSS Statistics | 16.8% |
| IBM SPSS Modeler | 16.5% |
| Other | 59.2% |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 3 |
| Large Enterprise | 4 |
| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 33 |
| Large Enterprise | 62 |
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.
SAS Enterprise Miner was previously known as Enterprise Miner.
| Author info | Rating | Review Summary |
|---|---|---|
| Executive Head of analytics at a retailer with 5,001-10,000 employees | 4.5 | I use SAS Enterprise Miner for predictive analytics, benefiting from its visual data pipeline. However, it needs better integration with cloud-native technologies to enhance its effectiveness in structured and unstructured data mining. |
| Executive Head of analytics at a retailer with 5,001-10,000 employees | 4.0 | I use SAS Enterprise Miner primarily for data management and analytics, and its integration is excellent. However, it is very costly and not suitable for small businesses. Technical support also needs improvement. |
| Head Of Risk Management at a financial services firm with 11-50 employees | 4.0 | I use this for fraud modeling; it's easy to use with great data extraction and automation. However, the initial setup is challenging, and I'd like improved SQL compatibility and consolidated product offerings. |
| Senior Systems Engineer at a financial services firm with 10,001+ employees | 2.5 | I use SAS for analytics, appreciating its good technical support. Yet, it's overly complex, I dislike its protocols, and it's expensive. I'm actively seeking open-source alternatives like Anaconda due to these challenges. |
| Professor at a university with 1,001-5,000 employees | 4.5 | I find SAS Enterprise Miner excellent for research, especially handling large data and complex clustering. It's stable, scalable, and setup was easy. While I rate it 9/10, tutorials would benefit others. |
| Business Intelligence Developer at a media company with 1,001-5,000 employees | 4.0 | I use SAS Enterprise Miner for predictive analytics, valuing its multi-algorithm comparison. Setup was complex and expensive, and I want improved visualization and UI. It's stable, and I rated it 8/10. |
| Data Analyst at a financial services firm with 201-500 employees | 4.0 | I rate this a good solution for ad hoc analysis, valuing its decision tree creation and interface. However, I find its ease of use and initial setup complex, needing better compatibility and visualization, despite its stability. |
| Analytics Lead at Pegasus | 4.0 | I’ve used this robust solution for four years, appreciating its data analysis and flexibility over IBM. Yet, I feel it needs better speed, virtualization, and fairer text analytics licensing, as its overall cost is high. |
