Compare IBM SPSS Statistics vs. SAS Enterprise Miner

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Most Helpful Review
Find out what your peers are saying about IBM SPSS Statistics vs. SAS Enterprise Miner and other solutions. Updated: May 2021.
512,221 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"Most of the product features are good but I particularly like the linear regression analysis.""Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files.""The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important.""You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use.""They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do.""It has the ability to easily change any variable in our research.""The most valuable feature is the user interface because you don't need to write code.""In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

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"The setup is straightforward. Deployment doesn't take more than 30 minutes.""The solution is very good for data mining or any mining issues.""he solution is scalable.""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 most valuable feature is the decision tree creation.""The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them.""Good data management and analytics.""The solution is able to handle quite large amounts of data beautifully."

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Cons
"I think the visualization and charting should be changed and made easier and more effective.""Technical support needs some improvement, as they do not respond as quickly as we would like.""The statistics should be more self-explanatory with detailed automated reports.""Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.""The product should provide more ways to import data and export results that are user-friendly for high-level executives.""The design of the experience can be improved.""This solution is not suitable for use with Big Data.""Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."

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"The user interface of the solution needs improvement. It needs to be more visual.""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.""The solution needs an easier interface for the user. The user experience isn't so easy for our clients.""Virtualization could be much better.""The ease of use can be improved. When you are new it seems a bit complex.""The visualization of the models is not very attractive, so the graphics should be improved.""Technical support could be improved.""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."

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Pricing and Cost Advice
"We think that IBM SPSS is expensive for this function.""The price of this solution is a little bit high, which was a problem for my company.""The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

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"This solution is for large corporations because not everybody can afford it.""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."

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Questions from the Community
Top Answer: You can quickly build models because it does the work for you.
Top Answer: In comparing the price of other products, SPSS Statistics is too expensive. Even when most of the universities in the Middle East have licenses for SPSS Statistics, they do not have licenses for the… more »
Top Answer: The technical support should be improved.
Top Answer: The technical support is very good.
Top Answer: We'd prefer it if the solution was open source. That would make it less expensive.
Top Answer: We really don't like the protocols the solution offers. The solution is much more complex than other options.
Ranking
2nd
out of 16 in Data Mining
Views
4,039
Comparisons
3,128
Reviews
15
Average Words per Review
720
Rating
7.9
4th
out of 16 in Data Mining
Views
3,185
Comparisons
2,424
Reviews
10
Average Words per Review
391
Rating
7.5
Popular Comparisons
Also Known As
SPSS Statistics
Enterprise Miner
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Overview
Your organization has more data than ever, but spreadsheets and basic statistical analysis tools limit its usefulness. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next. Virtually eliminate time-consuming data prep; and quickly create, manipulate and distribute insights for decision making.
SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.
Offer
Learn more about IBM SPSS Statistics
Learn more about SAS Enterprise Miner
Sample Customers
LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Top Industries
REVIEWERS
University29%
Financial Services Firm21%
Aerospace/Defense Firm7%
Non Profit7%
VISITORS READING REVIEWS
Comms Service Provider26%
Computer Software Company15%
Educational Organization14%
Government6%
REVIEWERS
Financial Services Firm57%
Media Company14%
Retailer14%
University14%
VISITORS READING REVIEWS
Computer Software Company24%
Comms Service Provider13%
Financial Services Firm12%
Government6%
Company Size
REVIEWERS
Small Business28%
Midsize Enterprise22%
Large Enterprise50%
REVIEWERS
Small Business25%
Midsize Enterprise33%
Large Enterprise42%
Find out what your peers are saying about IBM SPSS Statistics vs. SAS Enterprise Miner and other solutions. Updated: May 2021.
512,221 professionals have used our research since 2012.

IBM SPSS Statistics is ranked 2nd in Data Mining with 15 reviews while SAS Enterprise Miner is ranked 4th in Data Mining with 10 reviews. IBM SPSS Statistics is rated 8.0, while SAS Enterprise Miner is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". On the other hand, the top reviewer of SAS Enterprise Miner writes "Good GUI, an easy initial setup, and very flexible". IBM SPSS Statistics is most compared with IBM SPSS Modeler, TIBCO Statistica, Weka, MathWorks Matlab and KNIME, whereas SAS Enterprise Miner is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio, RapidMiner, SAS Visual Analytics and Altair Knowledge Studio. See our IBM SPSS Statistics vs. SAS Enterprise Miner report.

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