Compare IBM SPSS Modeler vs. IBM Watson Studio

IBM SPSS Modeler is ranked 3rd in Data Science Platforms with 16 reviews while IBM Watson Studio is ranked 10th in Data Science Platforms with 6 reviews. IBM SPSS Modeler is rated 8.2, while IBM Watson Studio is rated 8.4. The top reviewer of IBM SPSS Modeler writes "Ease of use, the user interface, is the best part; the ability to customize streams with R and Python is useful". On the other hand, the top reviewer of IBM Watson Studio writes "It has greatly improved the performance because it is standardized across the company". IBM SPSS Modeler is most compared with KNIME, Alteryx and IBM Watson Studio, whereas IBM Watson Studio is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio and Amazon SageMaker. See our IBM SPSS Modeler vs. IBM Watson Studio report.
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Most Helpful Review
Find out what your peers are saying about IBM SPSS Modeler vs. IBM Watson Studio and other solutions. Updated: January 2020.
398,050 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:

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.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.New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data.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 itThe 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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The system's ability to take a look at data, segment it and then use that data very differently.The scalability of IBM Watson Studio is great.The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video.The solution is very easy to use.It is a stable, reliable product.Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic.The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people.It has greatly improved the performance because it is standardized across the company.

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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.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.The standard package (personal) is not supported for database connection.Unstructured data is not appropriate for SPSS Modeler.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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It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs.The decision making in their decision making feature is less good than other options.So a better user interface could be very helpfulMore features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier.We would like to see it more web-based with more functionality.We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers.Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge.

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Pricing and Cost Advice
When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount.It got us a good amount of money with quick and efficient modeling.The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool.It is a huge increase to time savings.

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Compared 18% of the time.
Compared 15% of the time.
Also Known As
SPSS ModelerWatson Studio, IBM Data Science Experience, Data Science Experience, DSx

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

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IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

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Sample Customers
Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis TurkeyGroupM, Accenture, Fifth Third Bank
Top Industries
Financial Services Firm24%
Manufacturing Company14%
Software R&D Company21%
Comms Service Provider13%
Financial Services Firm11%
Software R&D Company39%
Comms Service Provider11%
Media Company4%
Find out what your peers are saying about IBM SPSS Modeler vs. IBM Watson Studio and other solutions. Updated: January 2020.
398,050 professionals have used our research since 2012.
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