Compare Alteryx vs. IBM SPSS Modeler

Alteryx is ranked 1st in Data Science Platforms with 9 reviews while IBM SPSS Modeler is ranked 2nd in Data Science Platforms with 23 reviews. Alteryx is rated 9.2, while IBM SPSS Modeler is rated 8.0. The top reviewer of Alteryx writes "Speeds up the time to obtain business answers/insights on data". On the other hand, 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". Alteryx is most compared with KNIME, Dataiku Data Science Studio and Microsoft BI, whereas IBM SPSS Modeler is most compared with KNIME, Alteryx and IBM Watson Studio. See our Alteryx vs. IBM SPSS Modeler report.
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Alteryx Logo
25,558 views|20,013 comparisons
IBM SPSS Modeler Logo
9,664 views|7,402 comparisons
Most Helpful Review
Find out what your peers are saying about Alteryx vs. IBM SPSS Modeler and other solutions. Updated: September 2019.
366,486 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
Shortens the time required to start analyzing data and looking for insights, minimizing the tasks that do not add value to the business and maximizing the analysis phase.Alteryx speeds up the time to obtain business answers/insights on data.It is one of the most complete and great customer service that I experienced with a software company/ecosystem.The tools are built-in. You just plug and play, drag and drop, once you understand how to use the tools, it is easy.It helps clean messy data and provides spatial analysis.It saves time on a lot projects. ​The analytics are easy​.It allows for manipulation and automation, which has greatly reduced the amount of time required per project.

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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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Cons
Even when it already includes some AI models, this area could be improved.It would be great to create the final users' visualization within Alteryx.I think better visualization would be helpful to this solution.It is a little bit pricey.It seems to me that it is not always user friendly.Alteryx could be improved in the area of analytics and central governance.The next feature release should include easier reporting.In the database, it should be more functional and connect to more big data, especially using IPI.

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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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Pricing and Cost Advice
Opt for the three year subscription. It is 20% less than the yearly one.ROI is huge. There are some secondary benefits, like analysts getting their post 5 PM time back or the ability to shorten all closing processes to a half or less.It is $4,000 a year, so it is cheap versus other solutions. It also accomplishes three times the volume on the job in the same time (as the other solutions).​It can be a bit pricey, especially after the first year.The seat is too expensive.​Very transparent.​

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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.If you are in a university and the license is free then you can use the tool without any charges, which is good.Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers.

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report
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366,486 professionals have used our research since 2012.
Ranking
1st
Views
25,558
Comparisons
20,013
Reviews
9
Average Words per Review
232
Avg. Rating
9.2
2nd
Views
9,664
Comparisons
7,402
Reviews
23
Average Words per Review
458
Avg. Rating
8.1
Top Comparisons
Compared 31% of the time.
Compared 6% of the time.
Compared 18% of the time.
Compared 13% of the time.
Also Known As
SPSS Modeler
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Alteryx
IBM
Overview

Alteryx is a self-service data analytics solution, that provides a platform that can prep, blend, and analyze all of your data, then deploy and share analytics in hours. It can automate time-consuming and manual data tasks while performing predictive, statistical, and spatial analytics in the same workflow. It uses a drag and drop tool with an intuitive user interface with no coding and programming required. Alteryx licenses are subscription-based and include all product updates and support to their customers.

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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Sample Customers
AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy QueenReisebªro 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 Turkey
Top Industries
REVIEWERS
Manufacturing Company13%
Healthcare Company13%
Financial Services Firm13%
Energy/Utilities Company13%
VISITORS READING REVIEWS
Financial Services Firm22%
Software R&D Company14%
Manufacturing Company12%
Comms Service Provider7%
REVIEWERS
Financial Services Firm25%
Manufacturing Company15%
Healthcare Company10%
Government10%
VISITORS READING REVIEWS
Financial Services Firm20%
Software R&D Company16%
University10%
Government5%
Find out what your peers are saying about Alteryx vs. IBM SPSS Modeler and other solutions. Updated: September 2019.
366,486 professionals have used our research since 2012.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
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