Compare Alteryx vs. IBM SPSS Modeler
Alteryx is ranked 1st in Data Science Platforms with 14 reviews while IBM SPSS Modeler is ranked 3rd in Data Science Platforms with 16 reviews. Alteryx is rated 8.8, while IBM SPSS Modeler is rated 8.2. The top reviewer of Alteryx writes "Does a good job of end-to-end integration as well as accessing data from multiple sources or email modes". 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.
Most Helpful Review | |||
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 Find out what your peers are saying about Alteryx vs. IBM SPSS Modeler and other solutions. Updated: January 2020. 399,757 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 | |
Alteryx has made us more agile and increased the speed and effectiveness of decision making. The ease-of-use allows non-technical business users to directly create their own solutions without the use of additional development resources. This is a drag-and-drop tool which is easy-to-use and yet can be customized by creating your own components. The solution offers excellent predicting power. The accuracy and confidence have been great. The product is very stable and super fast, five-star. It's significantly more stable than it's nearest competitor. Alteryx is so advanced. It's just drag and drop. 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. | 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 it 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. |
Cons | |
The server is too expensive for what you get and it really a designer desktop on a server. There is currently no cloud solution and this would be valuable for many clients. The GUI interface functions but it could stand to be updated to a more modern look and feel. The solution could work on the BI side of the tool to make it a bit better. The only area where the product lags is documentation and videos on the analytical app and the batch macro. It would be great if Alteryx could take third party tools and incorporate them. 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. | 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. |
Pricing and Cost Advice | |
We have a yearly cost that we pay for the licensing. We do not pay any costs in addition to the licensing fees. The pricing is $5000 per year per production license. 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. | 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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Answers from the Community | |||
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Ranking  | |||
Views 30,132 Comparisons 23,861 Reviews 13 Average Words per Review 399 Avg. Rating 8.9 | Views 9,691 Comparisons 7,421 Reviews 17 Average Words per Review 496 Avg. Rating 8.2 | ||
Top Comparisons | |||
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Also Known As | |||
| SPSS Modeler | |||
Learn | |||
| 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. Buy | ||
Offer | |||
Learn more about Alteryx | Learn more about IBM SPSS Modeler | ||
Sample Customers | |||
| AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen | 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 Turkey | ||
Top Industries | |||
Software R&D Company15% Non Tech Company15% Hospitality Company8% Healthcare Company8% Software R&D Company25% Financial Services Firm14% Comms Service Provider11% Manufacturing Company7% | Financial Services Firm24% University14% Manufacturing Company14% Healthcare Company10% Software R&D Company22% Comms Service Provider13% Financial Services Firm11% Government9% | ||
Company Size | |||
Small Business48% Midsize Enterprise15% Large Enterprise37% Small Business15% Midsize Enterprise8% Large Enterprise77% | Small Business29% Midsize Enterprise11% Large Enterprise61% | ||
Find out what your peers are saying about Alteryx vs. IBM SPSS Modeler and other solutions. Updated: January 2020.
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One of the differences is that with Alteryx you can use it as an ETL and analytics tool.
Please connect with me directly if you want to know more.
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, R integrations if your team requires this.
It can handle over 2 billion rows of data in its in-memory engine on a notebook without requiring a server, thus it's cheaper. It has a much better community than IBM that you can get your answers pretty clear and fast if you need it.
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products.
Regarding Alteryx I can say the following:
- An excellent desktop tool for Data Prep and analytics.
- Feature-rich and convenient user interface.
- However, it is implemented in C#, therefore works in MS Windows environment only. Mac or Linux users can’t use it. Interface with Apache Spark implemented via special plugin (do not remember details), which results in 2-hop data transfer. It may negatively affect performance.
I am unfamiliar with the IBM SPSS Modeler but use KNIME and Alteryx for different projects. Alteryx is an excellent, very easy to get started with and get to results data cleansing, ETL, analytics, geospatial modeling, predictive analytics. I build reusable macros in Alteryx, use flexible inputs for what-if modeling, feed information to Power BI or Tableau. It seems price competitive against SPSS.