SAS Enterprise Miner

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
SAS Enterprise Miner
Score 9.0 out of 10
N/A
SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.N/A
Pricing
SAS Enterprise Miner
Editions & Modules
No answers on this topic
Offerings
Pricing Offerings
SAS Enterprise Miner
Free Trial
No
Free/Freemium Version
No
Premium Consulting/Integration Services
No
Entry-level Setup FeeNo setup fee
Additional Details
More Pricing Information
Community Pulse
SAS Enterprise Miner
Features
SAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
SAS Enterprise Miner
8.8
Ratings
5% above category average
Connect to Multiple Data Sources8.10 Ratings
Extend Existing Data Sources9.00 Ratings
Automatic Data Format Detection9.30 Ratings
MDM Integration9.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
SAS Enterprise Miner
8.1
Ratings
3% below category average
Visualization7.10 Ratings
Interactive Data Analysis9.10 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
SAS Enterprise Miner
8.0
Ratings
2% below category average
Interactive Data Cleaning and Enrichment7.80 Ratings
Data Transformations8.20 Ratings
Data Encryption8.10 Ratings
Built-in Processors8.10 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
SAS Enterprise Miner
8.8
Ratings
5% above category average
Multiple Model Development Languages and Tools7.50 Ratings
Automated Machine Learning9.80 Ratings
Single platform for multiple model development8.50 Ratings
Self-Service Model Delivery9.20 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
SAS Enterprise Miner
7.8
Ratings
9% below category average
Flexible Model Publishing Options7.00 Ratings
Security, Governance, and Cost Controls8.50 Ratings
Best Alternatives
SAS Enterprise Miner
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternatives
User Ratings
SAS Enterprise Miner
Likelihood to Recommend
9.9
(0 ratings)
Support Rating
10.0
(0 ratings)
User Testimonials
SAS Enterprise Miner
Likelihood to Recommend
Text Miner option is very useful to uncover trending themes in very large data sets.
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Pros
  • Developing and evaluating ensemble models.
  • A very transparent interface.
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Cons
  • One of the major flaws is that the tool is basically an interface to SAS/STAT code. It generates code in the background and runs it. Because of that, some errors are warning might be a little difficult to understand for users who aren't proficient with SAS code.
  • R integration is nice but I would like to see the possibility to integrate even more statistical models different than SAS. That would allow for better performance optimization when really required.
  • The light client is java based and a little heavy on the OS. It would be nice to get a web-based version of the tool instead of the java one.
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Support Rating
I have contacted SAS twice in the past year and they have been super responsive both times. They solved my problem. I am also registered for an in-person class next month and they called today to tell me that it will be an online-only session. They apologized for the change and registered me for the online version. Super helpful!
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Alternatives Considered
For those that are used to the SAS ecosystem, SAS Enterprise Miner is a massive move in the right direction. It makes doing analytics much more enjoyable. It is more user-friendly than Spotfire or Kinesis and seems to produce better results overall. SAS Enterprise Miner seems to be written by analysts for analysts.
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Return on Investment
  • It has a positive ROI to our business, as our sales lead rate increased after we started recommending SAS EM.
  • Our business operation numbers improved after we introduced SAS EM and started using predictive analytics for our customer retention and customer chain prediction.
  • The statistical modelling for the risk controls in our financial department helped to reduce the related residual risk.
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ScreenShots