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SAS Enterprise Miner

SAS Enterprise Miner

Overview

What is SAS Enterprise Miner?

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.

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Recent Reviews

TrustRadius Insights

Users of the software have found it to be versatile and powerful, with a wide range of use cases. From data analysis in academic journals …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 16 features
  • Automatic Data Format Detection (5)
    9.3
    93%
  • Extend Existing Data Sources (5)
    9.0
    90%
  • Connect to Multiple Data Sources (5)
    8.1
    81%
  • Visualization (5)
    7.1
    71%
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Pricing

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N/A
Unavailable

What is SAS Enterprise Miner?

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.

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  • No setup fee

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  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Features

Platform Connectivity

Ability to connect to a wide variety of data sources

8.8
Avg 8.5

Data Exploration

Ability to explore data and develop insights

8.1
Avg 8.4

Data Preparation

Ability to prepare data for analysis

8
Avg 8.2

Platform Data Modeling

Building predictive data models

8.8
Avg 8.5

Model Deployment

Tools for deploying models into production

7.8
Avg 8.6
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Product Details

What is SAS Enterprise Miner?

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.

Business users and subject-matter experts with limited statistical skills can generate their own models using SAS Rapid Predictive Modeler. Its GUI steps them through a workflow of data mining tasks. Analytics results are displayed in easy-to-understand charts that provide the needed insights.

SAS Enterprise Miner Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

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.

Reviewers rate Automated Machine Learning highest, with a score of 9.9.

The most common users of SAS Enterprise Miner are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(11)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Users of the software have found it to be versatile and powerful, with a wide range of use cases. From data analysis in academic journals to risk modeling in the banking industry, this software has proven to be a valuable tool for solving various business problems. It has been used by students for lecture assignments and major projects, as well as by professionals in the financial services sector for credit risk models, propensity models, and decision trees for client segmentation.

One notable feature is the software's ability to build complex data mining and statistical models quickly and easily. Users have praised its simplicity in determining important variables for pricing models, making it ideal for researchers and analysts. Additionally, the software allows users to build multiple predictive models and efficiently compare results, helping them make informed decisions and increase their return on investment.

Furthermore, the software's flexibility in model selection and its accuracy in producing forecasts have made it a leading analytics solution in the market. The graphical analysis provided by the software is often considered cleaner compared to other products, enhancing the user experience and facilitating insights. Whether it's analyzing large volumes of claims, performing sentiment analysis, or creating scoring models for prediction, users have found this software to be a reliable and efficient tool for solving statistical problems and extracting valuable insights from data.

Overall, customers recommend this software for its performance across various industries and business functions. It has proven to be an indispensable tool in improving decision-making processes, enhancing internal efficiencies, and gaining valuable insights from data analysis.

Easy to Use and Accurate: Users found SAS Enterprise Miner easy to use and accurate, with the ability to handle multiple data sources effectively. Several reviewers mentioned this as a positive aspect of the software.

Wide Range of Algorithm Choices: Users appreciated the wide range of algorithm choices available in SAS Enterprise Miner. They mentioned that it includes various options for data mining tasks such as random, neural networks, support vectors, ensemble modeling, and more. This was stated by many users.

Top-Class Customer Support: Users praised the customer support provided by SAS for Enterprise Miner. They mentioned that it is top class and helpful when they encountered any issues or had questions about using the software. A significant number of reviewers highlighted this aspect.

Difficult to Learn: Several users have found the software difficult to learn, requiring hours of effort and training. They mentioned that it is not easy to grasp the nuances of each model, especially for someone with a stats background.

Outdated Interface: Many users expressed their dissatisfaction with the software's interface, describing it as old-school and not updated with trendy methods. They felt that the dashboard and interface were outdated, clunky, and not user-friendly.

Expensive and Difficult to Obtain: Users mentioned that the software is expensive and can be challenging to obtain, particularly for students or small businesses. Some reviewers also pointed out that it takes time to gain access to SAS tools and is costly compared to other data analysis software on the market.

Users have made several recommendations based on their experiences with SAS Enterprise Miner. First, it is recommended to request a demo session and prepare specific questions to address business problems before making a decision. This allows users to fully evaluate the software's capabilities and determine if it aligns with their needs. Second, users suggest trying both R and SAS Enterprise Miner free trials to determine which software is better suited for their data needs. This allows for a comparison of the features and functionalities offered by each option. Lastly, incorporating open source languages within SAS Enterprise Miner is advised. This recommendation aims to enhance the software's flexibility and expand its capabilities by leveraging additional tools and resources.

Attribute Ratings

Reviews

(1-5 of 5)
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Score 10 out of 10
Vetted Review
Verified User
Incentivized
SAS Miner is used across the organization. The software is used for two main purposes. First, SAS Enterprise Miner is perhaps the most useful software in the world for ensemble modeling. Second, SAS Enterprise Miner makes producing reproducible models in an efficient structure about as easy as it can get.
  • Developing and evaluating ensemble models.
  • A very transparent interface.
  • SAS Enterprise Miner is far from the fastest software out there
  • Integrating SAS Enterprise Miner with other software tools is not easy.
SAS Enterprise Miner is world-class software for individuals interested in developing reproducible models in a reasonable amount of time. Perhaps the most useful part of SAS Enterprise Miner is the ability to compare models with other models without writing code. The ensemble modeling capabilities is the easiest way to do ensemble modeling I have come across. SAS Enterprise Miner is well-suited for beginning to advanced analysts who know something about advanced analytics. The software is not well-suited for analysts or companies that have little interest in advanced modeling.
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
90%
9.0
MDM Integration
90%
9.0
Data Exploration (2)
90%
9.0
Visualization
80%
8.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
85%
8.5
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
80%
8.0
Built-in Processors
80%
8.0
Platform Data Modeling (4)
92.5%
9.3
Multiple Model Development Languages and Tools
80%
8.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
90%
9.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
90%
9.0
  • SAS Enterprise Miner is a positive ROI in the sense that it saves a ton of time coding.
  • SAS Enterprise Miner is a negative ROI in that it's expensive, and perhaps makes analysts brainless.
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.
SAS' customer support used to be non-existent many years ago. Today, contacting SAS customer support is great. They are responsible, knowledgable, and seem to have an interest in getting the results right the first time. With that said, Enterprise Miner's online support is weak, probably because the user base is much smaller than other tools.
Gary Wilcox | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
I use SAS Enterprise Miner regularly to conduct data analysis for articles published in academic journals. It is great respondings software that has multiple options. I mostly use Text Miner as a tool to uncover themes in large amounts of unstructured data. It rarely crashes and is able to handle very large files.
  • Enterprise Miner has many different data analysis options.
  • It is easy to use and very reliable.
  • The algorithms behind this statistical software are world class.
  • SAS is not as user friendly as other stats software.
Text Miner option is very useful to uncover trending themes in very large data sets.
Platform Connectivity (4)
67.5%
6.8
Connect to Multiple Data Sources
80%
8.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
100%
10.0
MDM Integration
N/A
N/A
Data Exploration (2)
70%
7.0
Visualization
60%
6.0
Interactive Data Analysis
80%
8.0
Data Preparation (4)
32.5%
3.3
Interactive Data Cleaning and Enrichment
60%
6.0
Data Transformations
70%
7.0
Data Encryption
N/A
N/A
Built-in Processors
N/A
N/A
Platform Data Modeling (4)
57.5%
5.8
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
N/A
N/A
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
80%
8.0
Model Deployment (2)
75%
7.5
Flexible Model Publishing Options
70%
7.0
Security, Governance, and Cost Controls
80%
8.0
  • It has made me a more productive scholar enabling me to interact with a wider range of academic disciplines.
  • SAS is always well respected in the journal I publish in.
  • It is very reasonable to get a yearly license through the university where I work.
  • PITA to re-install.
I like the algorithms SAS uses better than SPSS. I have been writing SAS code since the mid 1980s and trust their development team. Also offer great refresher class to academics.
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!
Akos Krommer, CISA, ACDA | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
SAS Enterprise Miner is used by my department for smaller machine learning models (clustering) and predictive analytics (future churn rate calculation), as well as data exploration and pattern analysis. We use the tool as well as recommend it for clients to help them improve business decision making (e.g loan decision making) and internal efficiencies.
  • Very easy to use and intuitive.
  • High performance.
  • Open source integration with R.
  • Amazing data science models.
  • Very good data preparation and exploration toolkit.
  • Still the same, very old and clunky GUI.
  • For smaller organizations, it can be quite pricey.
  • For less experienced users, the software can be a little overwhelming.
It does particularly well, where there is a need for analyzing very large datasets (e.g. large volume of claims) and the characteristics across things like insurance policies. It is performing very well with predictive analytical models (e.g. credit card defaults) or enhanced pattern analysis. However, in cases where reporting is important or where it is important that the model is easy to interpret this product may not be well suited.
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
80%
8.0
MDM Integration
90%
9.0
Data Exploration (2)
70%
7.0
Visualization
50%
5.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
90%
9.0
Interactive Data Cleaning and Enrichment
90%
9.0
Data Transformations
90%
9.0
Data Encryption
90%
9.0
Built-in Processors
90%
9.0
Platform Data Modeling (4)
80%
8.0
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
80%
8.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
80%
8.0
  • 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.
SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data preparation capabilities compared to the other tools we used.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Enterprise Miner is being used mostly in the Risk department and marketing department. For Marketing, it is used to develop different marketing decision making algorithms (mostly cross-sell, upsell, churn and acquisition models). These tasks help answer the following questions:
  • What are my customers next best action (what product would they consider)
  • Who is more likely to leave for a competitor
  • Who is more likely to increase their volume of savings and by how much.
For Risk, the use mostly measures the exposure to loss of the bank regarding loans. It will help answer the following questions:
  • How much money can I safely lend customers based on several metrics such as credit score rating, assets, ... (credit scorecards)
  • In case of recessions or the collapse of a specific industry, what is the change of global exposure at default based on the change in risk (IFRS9 stresstesting)
  • What is the risk of customers with overdue payment to never pay what they owe (Bad debt)
  • Is a customer doing money laundering or terrorist financing (Anti-money laundering)
  • Enterprise Miner is really visual and lets you do a whole lot without actually going into the detailed options. For decent results, you should really explore the different advanced options though.
  • The recent versions of Miner allow users to use R code in Miner. You can then compare several models and approach to get the best performing model.
  • The resulting data is really well displayed and easy to understand (ex: the lift graph, score ranking, etc.)
  • Miner has the ability to integrate custom SAS code which allows the user to add functionalities that are specific to the project.
  • 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.
This product might be suited where SAS is already present and widely used by analysts, where source data (for model development) is in SAS format (SAS table), or where you want to develop good models but maybe not the most optimal one. This product might not be a good fit if you barely have any SAS knowledge in the organization and don't wish to develop it, have other modeling software that you would like to integrate with it (other than R), or want a cheap and quick to implement solution for a small organization.
Platform Connectivity (4)
65%
6.5
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
90%
9.0
MDM Integration
N/A
N/A
Data Exploration (2)
70%
7.0
Visualization
70%
7.0
Interactive Data Analysis
70%
7.0
Data Preparation (4)
35%
3.5
Interactive Data Cleaning and Enrichment
60%
6.0
Data Transformations
80%
8.0
Data Encryption
N/A
N/A
Built-in Processors
N/A
N/A
Platform Data Modeling (4)
27.5%
2.8
Multiple Model Development Languages and Tools
40%
4.0
Automated Machine Learning
N/A
N/A
Single platform for multiple model development
70%
7.0
Self-Service Model Delivery
N/A
N/A
Model Deployment (2)
40%
4.0
Flexible Model Publishing Options
40%
4.0
Security, Governance, and Cost Controls
40%
4.0
  • In our organization, users were using SAS already so the learning curve was really low. Within a few weeks after the implementation, the users were already delivering models developed with SAS Enterprise Miner. It is difficult to talk about ROI as models were already being developed before. It was mostly a change of technology and it was a smooth transition.
  • Going with Enterprise Miner came with migration from desktop use of SAS to a server use of SAS. This created a new role of SAS administrator. This was obviously a cost but as the use of SAS increased greatly, it was expected.
  • From a methodology standpoint, Enterprise Miner helped greatly in the documentation of the model development which was a requirement in a few groups such as the risk groups. Having a visual "GUI-like" approach to development, the flowchart or diagram of the project in Miner was able to give users a good understanding of the approach the analyst took to develop the model.
SPSS was used for model development before SAS in my organization. SAS brought a bigger more complete integrated solution than SPSS had.
It allowed users to easily prepare their data with SAS/Enterprise Guide and then use it with Enterprise Miner. The data preparation tools of SAS are really well integrated and I don't feel it was the case with SPSS (or at least from what I've heard).
30
Data scientists and some senior BI analysts that have some statistical knowledge and understanding.
4
The support for Enterprise Miner is mostly a technical support. Software support is covered by co-workers and online queries.
For the technical support, it doesn't really require an additional person to cover that. In our case, the SAS admins support all SAS softwares and Miner is just one of them.
Thomas Young | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
SAS Enterprise Miner is being used across the department for predictive analytics and advanced modeling. I think the flow diagrams make SAS Enterprise Miner the best software out there for producing reproducible forecasts and analytics across multiple users. In addition to predictive modeling, there is also advanced modeling comprising the machine learning, logit, ensemble modeling, and other techniques.
  • The flow diagram combined with point-and-click make SAS Enterprise Miner easy to learn and apply in practice.
  • The ability to convert the drag-and-drop models into actual SAS code makes customization easier, although not foolproof-easy.
  • I think perhaps the most desirable aspect of SAS Enterprise Miner is its ability to create ensemble models, and then the straightforward way of evaluating ensemble modeling.
  • With large data sets, SAS Enterprise Miner sometimes takes a long time to run. Sometimes you have to just leave your computer running while Enterprise Miner does its thing.
  • If you want complete control over the modeling framework, you have to take what Enterprise Miner does and customize it. SAS seems to be working hard on making things easier to customize, but it's not completely there yet.
  • The graphic capabilities of SAS Enterprise Miner leave a lot to be desired, especially in the era of self-service business intelligence software.
SAS Enterprise Miner is well-suited for situations where advanced analytics are needed. The software is particularly useful when you need to compare the reliability of, say, Support Vector Machines versus Random Forests. The ensemble modeling capabilities are unsurpassed. Implementing predictive models is also straight-forward.
Platform Connectivity (4)
87.5%
8.8
Connect to Multiple Data Sources
100%
10.0
Extend Existing Data Sources
80%
8.0
Automatic Data Format Detection
90%
9.0
MDM Integration
80%
8.0
Data Exploration (2)
80%
8.0
Visualization
60%
6.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
82.5%
8.3
Interactive Data Cleaning and Enrichment
100%
10.0
Data Transformations
90%
9.0
Data Encryption
70%
7.0
Built-in Processors
70%
7.0
Platform Data Modeling (4)
90%
9.0
Multiple Model Development Languages and Tools
70%
7.0
Automated Machine Learning
100%
10.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
90%
9.0
Model Deployment (2)
80%
8.0
Flexible Model Publishing Options
90%
9.0
Security, Governance, and Cost Controls
70%
7.0
  • SAS Enterprise Miner improved our forecasting models. I don't think competing software could have accomplished what we did with SAS Enterprise Miner in as little time.
  • SAS Enterprise Miner isn't cheap. The high cost makes it harder to justify the return on investment. Luckily for us, SAS Enterprise Miner makes it so easy to perform machine learning and ensemble models that the costs were justified.
  • Sometimes it takes time figuring out what SAS Enterprise Miner is doing. If you're a newbie to analytics, SAS Enterprise Miner is a great starting point as long as you're willing to figure out what SAS is doing. Taking Enterprise Miner's word for it didn't work sometimes.
I think SAS Enterprise Miner has three advantages. The software is the easiest of any to implement ensemble modeling and other machine learning models. The second advantage is the ability to connect Enterprise Miner activities to other software. The third advantage is the ease of reproducing results. On the con side, Enterprise Miner is expensive and requires a commitment to figure out SAS black box.
TIBCO Spotfire, TIBCO Spotfire Data Science (previously Alpine Data), QlikView, SAS Enterprise Guide, Microsoft Azure, Sisense, Alteryx Analytics
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