SAS Enterprise Miner vs. Wolfram Mathematica

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
Mathematica
Score 8.2 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
SAS Enterprise MinerWolfram Mathematica
Editions & Modules
No answers on this topic
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
SAS Enterprise MinerMathematica
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsDiscounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
More Pricing Information
Community Pulse
SAS Enterprise MinerWolfram Mathematica
Features
SAS Enterprise MinerWolfram Mathematica
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
SAS Enterprise Miner
8.8
Ratings
5% above category average
Wolfram Mathematica
-
Ratings
Connect to Multiple Data Sources8.10 Ratings00 Ratings
Extend Existing Data Sources9.00 Ratings00 Ratings
Automatic Data Format Detection9.30 Ratings00 Ratings
MDM Integration9.00 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
SAS Enterprise Miner
8.1
Ratings
3% below category average
Wolfram Mathematica
-
Ratings
Visualization7.10 Ratings00 Ratings
Interactive Data Analysis9.10 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
SAS Enterprise Miner
8.0
Ratings
2% below category average
Wolfram Mathematica
-
Ratings
Interactive Data Cleaning and Enrichment7.80 Ratings00 Ratings
Data Transformations8.20 Ratings00 Ratings
Data Encryption8.10 Ratings00 Ratings
Built-in Processors8.10 Ratings00 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
Wolfram Mathematica
-
Ratings
Multiple Model Development Languages and Tools7.50 Ratings00 Ratings
Automated Machine Learning9.80 Ratings00 Ratings
Single platform for multiple model development8.50 Ratings00 Ratings
Self-Service Model Delivery9.20 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
SAS Enterprise Miner
7.8
Ratings
9% below category average
Wolfram Mathematica
-
Ratings
Flexible Model Publishing Options7.00 Ratings00 Ratings
Security, Governance, and Cost Controls8.50 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
SAS Enterprise Miner
-
Ratings
Wolfram Mathematica
9.9
Ratings
16% above category average
Pixel Perfect reports00 Ratings9.80 Ratings
Customizable dashboards00 Ratings9.90 Ratings
Report Formatting Templates00 Ratings9.90 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
SAS Enterprise Miner
-
Ratings
Wolfram Mathematica
9.9
Ratings
22% above category average
Drill-down analysis00 Ratings9.90 Ratings
Formatting capabilities00 Ratings9.90 Ratings
Integration with R or other statistical packages00 Ratings9.90 Ratings
Report sharing and collaboration00 Ratings9.90 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
SAS Enterprise Miner
-
Ratings
Wolfram Mathematica
9.3
Ratings
10% above category average
Publish to Web00 Ratings9.90 Ratings
Publish to PDF00 Ratings9.00 Ratings
Report Versioning00 Ratings9.90 Ratings
Report Delivery Scheduling00 Ratings8.90 Ratings
Delivery to Remote Servers00 Ratings8.90 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
SAS Enterprise Miner
-
Ratings
Wolfram Mathematica
9.9
Ratings
20% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.90 Ratings
Location Analytics / Geographic Visualization00 Ratings9.90 Ratings
Predictive Analytics00 Ratings9.90 Ratings
Best Alternatives
SAS Enterprise MinerWolfram Mathematica
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Supermetrics
Supermetrics
Score 10.0 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Supermetrics
Supermetrics
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
Dataiku
Dataiku
Score 7.6 out of 10
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User Ratings
SAS Enterprise MinerWolfram Mathematica
Likelihood to Recommend
9.9
(0 ratings)
9.9
(0 ratings)
Support Rating
10.0
(0 ratings)
9.5
(0 ratings)
User Testimonials
SAS Enterprise MinerWolfram Mathematica
Likelihood to Recommend
Text Miner option is very useful to uncover trending themes in very large data sets.
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We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
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Pros
  • Developing and evaluating ensemble models.
  • A very transparent interface.
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  • Doing the analysis is very good, plotting the data, getting the insight from data using this is easy and output looks pretty good
  • Solving mathematical problems, with detailed solutions step by step (mainly calculus problems)
  • You can also query this knowledge engine in simple English. It has ability to interpret that and will give you answer accordingly
  • Nowadays, it provides API to use, so you can do image processing, video/audio using this
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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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  • Should include more libraries and functions.
  • Should include more functions that can be used in Machine Learning.
  • Should include more functions that can be used in Data Science.
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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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Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
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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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The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."
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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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  • Mathematica is our "go to" environment for developing solutions for our clients, so I suppose you could say that it is solely responsible for our revenues. On occasion we do use other platforms but Mathematica is a core component of our offer to clients.
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