MatLab is a predictive analytics and computing platform based on a proprietary programming language. MatLab is used across industry and academia.
$49
per student license
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
MATLAB
SAS Enterprise Miner
Editions & Modules
Student
$49
per student license
Home
$149
perpetual license
Education
$250
per year
Education
$500
perpetual license
Standard
$860
per year
Standard
2,150
perpetual license
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Offerings
Pricing Offerings
MATLAB
SAS Enterprise Miner
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
MATLAB
SAS Enterprise Miner
Features
MATLAB
SAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
MATLAB
-
Ratings
SAS Enterprise Miner
8.8
Ratings
5% above category average
Connect to Multiple Data Sources
00 Ratings
8.10 Ratings
Extend Existing Data Sources
00 Ratings
9.00 Ratings
Automatic Data Format Detection
00 Ratings
9.30 Ratings
MDM Integration
00 Ratings
9.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
MATLAB
-
Ratings
SAS Enterprise Miner
8.1
Ratings
3% below category average
Visualization
00 Ratings
7.10 Ratings
Interactive Data Analysis
00 Ratings
9.10 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
MATLAB
-
Ratings
SAS Enterprise Miner
8.0
Ratings
2% below category average
Interactive Data Cleaning and Enrichment
00 Ratings
7.80 Ratings
Data Transformations
00 Ratings
8.20 Ratings
Data Encryption
00 Ratings
8.10 Ratings
Built-in Processors
00 Ratings
8.10 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
MATLAB
-
Ratings
SAS Enterprise Miner
8.8
Ratings
5% above category average
Multiple Model Development Languages and Tools
00 Ratings
7.50 Ratings
Automated Machine Learning
00 Ratings
9.80 Ratings
Single platform for multiple model development
00 Ratings
8.50 Ratings
Self-Service Model Delivery
00 Ratings
9.20 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Engineering, mathematical modeling, and machine learning are all fields where MATLAB will shine. It's fast, reliable, and relatively easy to use. MATLAB is the de facto standard when it comes to producing high-quality plots. If you need to deal with large data sets, and not take forever processing them, MATLAB may very well be the tool for you!
Has robust and easy-to-use debugging tools that can help one identify problems in one's codes.
Rich, well-developed and efficient library of mathematical and statistical functions that one might need to develop models or perform statistical analysis.
A very active online user community that is a great resource in terms of seeking help when you hit a snag.
Great help literature (and sometimes videos too) on all tools making it possible for all to train themselves.
MATLAB should have a full free version (without time limit) in order to be more accessible and thus have a greater user community.
The idea of having toolboxes to work directly with hardware (microcontrollers, single-board computers) is great, but one can tell it isn't updated very frequently and there isn't as much documentation available as with more common resources.
Our organization had a lot of trouble getting our network licenses to work properly and there wasn't any local service provider that could help us get it to work faster.
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.
The best thing about MATLAB is the variety of research and development fields it supports. The reason for this rating is that it is best used for medical images enhancement and signal processing, it is also used for speech to text conversion. This tool server is best when the demand is for machine learning.
The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.
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!
The commands and coding language of MATLAB reads a lot more in plain English as opposed to all the periods and other special characters that are needed when typing in Python or Java. Additionally MATLAB has several different function packages that can solve all different categories of problems so you don't have to make a bunch of different code scrips from scratch.
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.
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.