SAS Enterprise Miner enables comprehensive data management and analytics, handling extensive data volumes with diverse algorithms for model creation. Its integration and flexibility in SAS code usage make it suitable for both enterprise and personal use.
| Product | Mindshare (%) |
|---|---|
| SAS Enterprise Miner | 7.8% |
| IBM SPSS Statistics | 16.2% |
| IBM SPSS Modeler | 16.0% |
| Other | 60.0% |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 3 |
| Large Enterprise | 4 |
| Company Size | Count |
|---|---|
| Small Business | 36 |
| Midsize Enterprise | 33 |
| Large Enterprise | 64 |
SAS Enterprise Miner is recognized for its data pipeline visualization, data processing, and statistical modeling capabilities. Its user-friendly GUI and automation support data mining tasks, decision tree creation, and clustering. However, improvements are needed in its interface visualization, affordability, technical support, and integration with languages like Python and cloud-native tech. Enhanced performance, visualization, and model development auditing, along with text analytics in the main license, are desirable upgrades. Integration with Microsoft SQL and combined offerings remains a priority.
What are SAS Enterprise Miner's most important features?SAS Enterprise Miner is applied across industries like banking, insurance, and healthcare for data mining, machine learning, and predictive analytics. It aids in activities such as text mining, fraud modeling, and forecasting model creation, handling structured and unstructured data, and performing ad hoc analysis to model business processes and analyze data clusters.
SAS Enterprise Miner was previously known as Enterprise Miner.
| Author info | Rating | Review Summary |
|---|---|---|
| Executive Head of analytics at a retailer with 5,001-10,000 employees | 4.5 | I use SAS Enterprise Miner for predictive analytics, benefiting from its visual data pipeline. However, it needs better integration with cloud-native technologies to enhance its effectiveness in structured and unstructured data mining. |
| Executive Head of analytics at a retailer with 5,001-10,000 employees | 4.0 | I use SAS Enterprise Miner primarily for data management and analytics, and its integration is excellent. However, it is very costly and not suitable for small businesses. Technical support also needs improvement. |
| Head Of Risk Management at a financial services firm with 11-50 employees | 4.0 | I use this for fraud modeling; it's easy to use with great data extraction and automation. However, the initial setup is challenging, and I'd like improved SQL compatibility and consolidated product offerings. |
| Senior Systems Engineer at a financial services firm with 10,001+ employees | 2.5 | I use SAS for analytics, appreciating its good technical support. Yet, it's overly complex, I dislike its protocols, and it's expensive. I'm actively seeking open-source alternatives like Anaconda due to these challenges. |
| Professor at a university with 1,001-5,000 employees | 4.5 | I find SAS Enterprise Miner excellent for research, especially handling large data and complex clustering. It's stable, scalable, and setup was easy. While I rate it 9/10, tutorials would benefit others. |
| Business Intelligence Developer at a media company with 1,001-5,000 employees | 4.0 | I use SAS Enterprise Miner for predictive analytics, valuing its multi-algorithm comparison. Setup was complex and expensive, and I want improved visualization and UI. It's stable, and I rated it 8/10. |
| Data Analyst at a financial services firm with 201-500 employees | 4.0 | I rate this a good solution for ad hoc analysis, valuing its decision tree creation and interface. However, I find its ease of use and initial setup complex, needing better compatibility and visualization, despite its stability. |
| Analytics Lead at Pegasus | 4.0 | I’ve used this robust solution for four years, appreciating its data analysis and flexibility over IBM. Yet, I feel it needs better speed, virtualization, and fairer text analytics licensing, as its overall cost is high. |
| Director at EBI | 3.5 | I use this solution for data mining and machine learning, appreciating its good data processing and scalability. However, its stability and accuracy aren't perfect, setup is difficult, and it needs Python integration to be more user-friendly for clients. |
| Senior Business Analyst at a financial services firm with 1,001-5,000 employees | 3.5 | I found SAS Miner good for data mining, but my old version lacked auditing and user-friendly data prep. Stability issues with Java required monthly restarts. We switched to FICO, recommending open-source. I rated it seven. |
We use the solution for predictive analytics to do structured and unstructured data mining.
I like the way the product visually shows the data pipeline.
The product must provide better integration with cloud-native technologies.
I have been using the solution for 20 years.
The product is very stable. I rate the stability a nine out of ten.
I rate the tool’s scalability an eight out of ten. It is easy to scale, but it is linked to costs. The more we scale it, the more expensive it becomes. Around ten people use the solution in our organization.
It is very easy to deploy the tool in the production environment. The solution is cloud-based.
We need a consultant to deploy the solution.
The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pricing a four on a scale of one to ten, where one is high, and ten is low.
Overall, I rate the product a nine out of ten.
I'm a user of this solution and our use case is mostly for data management and analytics. The solution is on a server with access to client applications. We have about 20 people who are direct users of this product. I'm the head of data engineering and we're customers of SAS Miner.
The most valuable feature of the solution is data management and analytics. They also have very good integration.
The main issue with the solution is the high cost, it's very expensive. You really need to be a corporate company to buy the software. Individuals or small businesses wouldn't be able to afford it. Technical support could also be improved.
I've been using this solution for many years.
The stability is good, I haven't experienced any glitches.
I haven't experienced any issues with scalability.
Technical support is average, they're not the best but they're okay. The response times can be slow. They're not always immediately available when you need them.
The initial setup was fairly straightforward, but there are definitely complexities involved there. To get the software depot you need to first download it, which is quite a big thing. You then need to go through the same process to update so you either need some help to get it done or just need to go and do it yourself. Deployment took a few days and we used the SAS guys to assist.
I would recommend this product but there are open source products like Python that can do the same thing for free. Solutions like Jupiter Notebooks and Anaconda are also available.
I would rate this product an eight out of ten.
The primary use case of the solution was to perform fraud modeling techniques for a financial institution.
I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks.
One improvement I would suggest is the compatibility with Microsoft SQL and to improve all communications to the solution.
For a future release, I would like for the solution to be combined with other product offerings as opposed to a lot of separate solutions. For example, Text Miner is a separate product. I have to spend additional money to purchase a license for Text Miner.
I have been using the solution for four years.
The stability of the solution depends on the machine that is being used to run it. For example, if the machine's RAM is low, then issues may arise when dealing with large amounts of data.
The solution helped me scale up several of my analytical projects.
The customer service/technical support for this solution was satisfactory.
The initial setup is challenging if doing it for the first time.
The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it.
Individuals using this solution should be familiar with analytical techniques before they start with Enterprise Miner. Additionally, they should know the difference between SAS and SQL and understand why are they are using one or the other.
SAS is not a software development tool. Most people think that they will create applications using SAS, which is not true. It is an analytical tool and helps automate some of your tasks.
We primarily just use the analytical tool section of the solution.
The stability is okay.
The technical support is very good.
We really don't like the protocols the solution offers.
The solution is much more complex than other options.
We've been using the solution for three or four years, however, it may have been a bit longer.
I don't recall having issues with stability. I can't recall if there are bugs or glitches.
I don't really know to much about the scalability of the solution. It's not something I generally dealt with.
I've contacted technical support in the past. I'd say they offer enough of a level of service to us. We're pretty satisfied with their level of service. SAS internal support is very qualified and if we have any issues, we contact them and trust that they can help.
We are thinking to replace SAS with something like Anaconda. Actually, we are using Anaconda with Jupyter NET, however, we need to collect more details about Anaconda and other open-source analytic tools that could replace SAS.
I don't have too much information on the initial setup, however, it's my understanding that it's quite complex.
We'd prefer it if the solution was open source. That would make it less expensive.
We're using Enterprise Guide simultaneously with Enterprise Miner.
From my perspective, I believe that open-source analytics tools are closer to fitting our needs. We prefer open-source options like Anaconda. They offer good support and features. Anaconda also integrates well with Jupyter NET, which is important for us.
Overall, on a scale from one to ten, I'd rate the solution at a five. If there were better protocols and wasn't as complex as it is, I'd rate it a bit higher.
I'm working on a research project and we're trying to create clusters of homogeneous residents with respect to their ability or their risk of generating pressure ulcers.
The solution is able to handle quite large amounts of data beautifully.
The modeling and the cluster analysis and the market-based analysis are the solution's most valuable aspects.
I like the flexibility in that I can put SAS code into Enterprise Miner nodes. I'm able to do everything I need to do, even if it's not part of Enterprise Miner. I can implement it using SAS code.
The GUI is good.
The initial setup is fairly easy to accomplish.
I don't know if there are any features this solution needs.
While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system.
I've been using the solution for many years. I don't know the exact number, however, I can safely say it's been more than five.
The stability of the solution is excellent. I've never witnessed any glitches or bugs. It doesn't crash or freeze. I've found it to be reliable.
I've never seen any limitations on the solution when it comes to scalability. However, I don't know what's possible. I don't know to what extent people might want to apply it, and whether it's going to be scalable or not. It suits my needs perfectly.
Dozens of people use the solution within my organization.
Although I have had issues on the solution in the past, I have never called technical support to assist me. I've always been able to handle them myself. Therefore, I can't speak to the quality of service.
I previously worked with SAS as a STAT package.
The initial setup is not complex. I find it to be quite straightforward.
I use it for research purposes and we use it to analyze research data. So it's not an ongoing deployment.
I work at a university, so the solution is maintained by the school. There is a tech services department that takes care of any maintenance required on the solution.
I handled the implementation myself. I didn't need an integrator or consultant to assist me in the process.
I don't deal with the pricing of the solution. I don't know what it costs the university.
I use the latest version of the solution.
For me, SAS Enterprise Miner is not a standalone product. It's an effective tool, however, for data mining, especially for large amounts of data.
I'd rate the solution nine out of ten.
The primary use was for predictive analytics and to create a forecasting model. I was also using it for reporting.
The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them.
The visualization of the models is not very attractive, so the graphics should be improved.
I would like to see the user interface improved a bit.
I have only been using SAS Enterprise Miner for a short time.
We have not had any major issues with stability.
I have not contacted technical support.
I have used different solutions for Visual Analytics, but they have been for personal use.
I would say that the initial setup was a bit complex and hard to understand in the beginning. Overall, it was not very easy and not very difficult.
The license is really expensive. This solution is for large corporations because not everybody can afford it. It is a little bit tricky because you have to buy a license for each and every component that you use. For example, we wanted to add a plugin and we needed to buy it, which makes this an expensive tool.
We did not deploy this solution for our customer. Rather, we used Enterprise Miner to create a solution that was operationalized for production.
I would rate this solution an eight out of ten.
At this time the primary use case of this solution for ad hoc analysis.
The most valuable feature is the decision tree creation.
I like the interface, I think that it's ok. It's useful and helps you complete the things that you need to with the modeling and the analysis.
The ease of use can be improved. When you are new it seems a bit complex.
The initial setup could be simplified. When you want to do something or you want to use a tool, it can be difficult to find where to go and to know what to click.
In the next release, I would like it to be more compatible with other products, and to have better visualization.
I have been using this solution for about a year and a half.
We are using the latest version.
This solution is stable.
The scalability is good enough.
I have not contacted technical support.
The initial setup is more complex than it is straightforward.
If they are sure of what they want to do with the product then it is more than enough. The important part is that you have to know what you want it to be used for.
Overall it is a good solution.
I would rate this solution an eight out of ten.
The solution can be used in any domain, including banking, insurance, health care, partitions, classifications, etc. It's basically a complete solution, that helps with data client consolidation.
It's a VSL service provider, so improvement to an organization depends on how the client designs the implementation for the plan. Clients would be better reviewers of how the solution has improved their organizations.
Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic.
The solution should be faster.
Virtualization could be much better.
The solution could add some freeware. The text analytics, for example, aren't there in the VSL version. It requires a separate license. It should be included in the main solution's license as it's a basic requirement. It's shouldn't cost extra.
I've been working with the solution for four years.
The stability of the solution is good. We've never found any issues. It's compatible through any open-source solution. It's also very flexible for us to use in any of the parameters, unlike a few other professional products that we have used. With RedHat, for example, there is not the flexibility of changing the parameters and we are forced to use one or two version features.
I haven't tried to scale because we don't have an extensive user base, so I can't speak to scalability.
We haven't been in touch with technical support, but the documentation is quite elaborate, so I don't believe we'll need to reach out to them that much.
We previously used IBM products. This solution is more flexible and robust.
The initial setup was complex, but the support for the solution is good, so it was an okay implementation.
Deployment times vary. If there's a device, the SAS administrator can set it up pretty fast. Otherwise, for a first time user, it takes a while. Having administrator services helps a lot.
The solution is quite expensive. The pricing is too high.
I'm a SAS Enterprise Miner certified professional. I'm both a consultant and a user of the solution.
Our company is using the on-premises deployment model, although we mostly use in-house products. I use the desktop version for our clients. We might use the Cloud, depending on what the client is comfortable with. Most of our clients are enterprises.
I'd advise others considering implementing the solution to look at the costs and licensing to see if it is within your organization's budget.
I'd rate the solution eight out of ten.
We primarily use the solution for data mining and machine learning.
It helps the organization to build the DS part easily.
The data processing of the solution is very good, easy to use, both for enterprise and personal use.
The solution needs a language integration like Python for the user with more efficiency programming; SAS is kind of a powerful tool in past years that focus in SAS environment. but Python is more open and popular, which will be more acceptable in today's data science area.
I've been using the solution for about ten years.
The stability isn't perfect. We have issues with accuracy. In some AI forecasting areas, and the accuracy is not as good as the clients need it to be.
The solution is scalable.
The technical support for the solution is okay.
The initial setup is not so easy. Not many clients know much about the AI, so it's difficult to educate our clients on AI tech in order to make them feel comfortable using the product once it's implemented. Deployment takes about three to six months.
We use the cloud deployment model.
Our clients want to use more popular and more open-source tools, so SAS isn't so popular in our region.
I'd rate the solution seven out of ten. I'd rate the solution higher if it was easier to use. Right now, it requires too much effort to explain the tool to clients.
We primarily use the solution for modeling and a lot of business processes with lots of data.
The solution is very good for data mining or any mining issues.
We are using a very old version of SAS Miner, so I'm not sure if my opinions would be relevant for many people as they may be out-of-date.
From my point of view, a useful feature that we need from this tool is a history of development. When a user develops a model, each step of development requires new steps, and we want to be able to audit all these steps due to our regulatory requirements in model development. In SAS, we just copy via a screenshot from the system and put it in some document that covers the relevant stage. I know other systems have a feature to audit all steps to show what the user has done through the entire process of developing a model. It would be a time saver for us.
The preparation of both the mining and modeling process could be improved. The solution requires data and will reflect data, but the preparation of the data is not useful for end-users. We ended up having to do the preparation in another tool.
I've been using the solution for ten years.
The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch.
I've never contacted SAS technical support as I'm not part of the technical department team. There's another department in our company that handles this.
The initial setup is pretty straightforward. You just have to install it on the server and the users can connect to the server to access it.
We handled the implementation ourselves.
We were using the on-premises deployment model, however recently we switched solutions and now we are using FICO instead of SAS.
I'd recommend an open-source product over SAS, as I believe them to be the future.
I'd rate the solution seven out of ten.
