Reviews (1-5 of 5)
December 16, 2019
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.
Read Thomas Young's full review
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.
November 13, 2019
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.
Read Gary Wilcox's full review
Text Miner option is very useful to uncover trending themes in very large data sets.
May 02, 2019
Score 8 out of 10
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.
Read Akos Krommer, CISA, ACDA's full review
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.
January 08, 2019
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.
Read Thomas Young's full review
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.
January 14, 2019
Score 9 out of 10
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.
- 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.
Read this authenticated review
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.
SAS Enterprise Miner Scorecard Summary
Feature Scorecard Summary
About SAS Enterprise Miner
Categories: Data Science
SAS Enterprise Miner Technical Details