The software is amazing that it can produce such advanced models with a very simple user interface. The benefits I saw was more accurate forecasts in a quarter of the time to set up models.

I find SAS Enterprise Miner to be the most advanced data mining software on the market. The software offers all sorts of data mining tasks, including random forest, neural networks, support vectors, ensemble modeling, and a host of other options. The drag and drop user interface is quite nice, and a long way from where base SAS software programming used to be.

The biggest downside is the cost. SAS Enterprise Miner is amazing for the ease of use and the forecasts it produces, but it isn't free. Of the data mining software on the market, it is one of the most expensive. Also, although the software is perfect for building a model, it requires some work to create a model with incoming, real-time data.

I use SAS almost exclusively for data generation in quantitative projects - the functionality and ease of data generation can't be beat once proficiency is achieved. SAS is also my go-to software for fitting multilevel (hierarchical) models - it can do almost (not quite) everything I've ever needed, and uses minimal code to do so. I have been using SAS throughout my career and would say it is the program I'm most comfortable working in, even for data management (although the data management functionality is mediocre, see comments below).

Three things: graphs, data management, and structural equation models. The SAS graphics are so basic, it takes a lot of programming to get them to look even remotely presentable. That's not to say the capability isn't there, it just isn't worth the trouble when there are so many better programs that easily produce beautiful plots. It's a pain to transfer between programs when I've done everything else in SAS to produce the graphics elsewhere. Also, data management in SAS is notoriously underwhelming. I would love to see some increased functionality in data management. Finally, SAS has (in my view) limited capability to fit structural equation models compared to other comparable programs - I'd use Mplus (popular in social sciences) or R to fit and interpret SEMs over SAS any day.

Helping students learn data analytics and predictive analytics

Works flawlessly if you know exactly what you're doing and how to use the software.

Really difficult to use, difficult to navigate, and GUI needs to be updated as well as the product documentation. I wish there were better tutorials online for the Enterprise Miner.

I am a student and have been learning this software from the past 2 months, so I am using it for my lecture assignments and a major project for this semester.

1. It is a superb tool for learning data mining and predictive analysis of data. 2. The tool allows you to understand, summarize and explore the data using multiple modelling techniques like linear regression, neural networks, association rules and clustering etc. 3. Personally, I understood the concept of decision trees easily while using the tool rather than just reading through the book provided during the lecture. 4. It also gives you details statistics information related to the data which can be easily understood by the various chart features available in it. 5. User Interface seems to be typical old software but it is easy to use once you understand it.

1. Data Source response time: I have noticed this issue so far that after you create the data source in a new project, it doesn't appear simultaneously on the left side menu. At times, you have to close the enterprise miner and reopen/refresh the project to see it in the menu above diagrams. 2. Value for money: I feel it is costly for students and yeah it also comes with license issues apart from the price paid to buy it. 3. Learning: It takes hours of efforts and training to learn the software. Not easy to learn in a week or so.

I have worked with SAS Enterprise Minerduring the last five years doing data mining and machine learning projects. SAS Enterprise Miner is a reliable and robust software that has allowed me to perform statistical analyzes in large databases. I work in the banking industry and the software has helped me to carry out models of credit risk, propensity and decision trees for segmentation of clients.

I like the large number of features it has implemented. There are many machine learning algorithms and they are very easy to use and parameter. You can also process large amounts of data without consuming excessive ram memory

The interface is not very intuitive and can be similar to old software. It has some problems in response speed, it may seem like slow software.