IBM SPSS Modeler Pros and Cons

IBM SPSS Modeler Pros

Business75a1
Business Intelligence Manager at a manufacturing company with 1,001-5,000 employees
The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that.
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ScottMiller
IT Specialist at a government with 51-200 employees
We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want.
It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python.
We have been able to do some predictive modeling with it
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Jerry Crabb
Director of Engineering at a logistics company with 1,001-5,000 employees
It scales. I have not run into any challenges where it will not perform.​
​It works fine. I have not had any stability issues; it is always up.​
We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python.
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Greg Michael
Dealer Analytics Product & Services Manager at a manufacturing company with 1,001-5,000 employees
It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms.
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Altan Atabarut, M Sc.
Founding Partner at Altdata Analytics
Automated modelling, classification, or clustering are very useful.
A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly.
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Ionut Brandusoiu, PhD
Quantitative Researcher at a financial services firm with 10,001+ employees
Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms.
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VpDataAn413c
Vp, Data And Analytics at a financial services firm with 1,001-5,000 employees
We use analytics with the visual modeling capability to leverage productivity improvements.
It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it
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Michael Mance
Analyst at a transportation company with 10,001+ employees
It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers.
So far, the stability has been rock solid.
It will scale up to anything we need.
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Miguel Villalobos
Director - Institute of Advanced Analytics at a financial services firm with 501-1,000 employees
It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful.
It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler.
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Clinicalda4a
Clinical Assistant Professor at a university
It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly.
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IBM SPSS Modeler Cons

Business75a1
Business Intelligence Manager at a manufacturing company with 1,001-5,000 employees
Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization.
I think mapping for geographic data would also be a really great thing to be able to use.
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ScottMiller
IT Specialist at a government with 51-200 employees
The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only.
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Jerry Crabb
Director of Engineering at a logistics company with 1,001-5,000 employees
​I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities.​
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353,012 professionals have used our research since 2012.
Altan Atabarut, M Sc.
Founding Partner at Altdata Analytics
Customer support is hard to contact.
It is not integrated with Qlik, Tableau, and Power BI.
Expensive to deploy solutions. You need to buy an extra deployment unit.
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Ionut Brandusoiu, PhD
Quantitative Researcher at a financial services firm with 10,001+ employees
It would be beneficial if the tool would include more well-known machine learning algorithms.
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Michael Mance
Analyst at a transportation company with 10,001+ employees
It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking.
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Miguel Villalobos
Director - Institute of Advanced Analytics at a financial services firm with 501-1,000 employees
I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it.
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Clinicalda4a
Clinical Assistant Professor at a university
When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems.
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Research9440
Research Assistant
If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement.
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UnitMana92c0
Unit Manager at a insurance company with 1,001-5,000 employees
It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler.
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Find out what your peers are saying about IBM, SAS, Knime and others in Data Mining. Updated: June 2019.
353,012 professionals have used our research since 2012.
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