Compare IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio

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Top Review
Find out what your peers are saying about IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: September 2021.
534,468 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
"Very good data aggregation.""It is a great product for running statistical analysis.""Automation is great and this product is very organized.""You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after.""The supervised models are valuable. It is also very organized and easy to use."

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"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure.""The most valuable feature is data normalization.""The UI is very user-friendly and that AI is easy to use.""The solution is very fast and simple for a data science solution.""Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills.""The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.""The AutoML is helpful when you're starting to explore the problem that you're trying to solve.""The interface is very intuitive."

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Cons
"Requires more development.""It would be good if IBM added help resources to the interface.""Dimension reduction should be classified separately.""When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing.""Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."

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"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice.""The data cleaning functionality is something that could be better and needs to be improved.""When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers.""The solution should be more customizable. There should be more algorithms.""A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer.""Integration with social media would be a valuable enhancement.""The AutoML feature is very basic and they should improve it by using a more robust algorithm.""The data preparation capabilities need to be improved."

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Pricing and Cost Advice
"$5,000 annually.""This tool, being an IBM product, is pretty expensive.""Its price is okay for a company, but for personal use, it is considered somewhat expensive."

More IBM SPSS Modeler Pricing and Cost Advice »

"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly.""From a developer's perspective, I find the price of this solution high.""The licensing cost is very cheap. It's less than $50 a month.""There is a license required for this solution.""I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."

More Microsoft Azure Machine Learning Studio Pricing and Cost Advice »

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Questions from the Community
Top Answer: There are some important differences between both products. So probably, the first question I'll ask you is "for what use case are you evaluating these products?" Of course, there are some general… more »
Top Answer: The supervised models are valuable. It is also very organized and easy to use.
Top Answer: Its price is okay for a company, but for personal use, it is considered somewhat expensive.
Top Answer: The initial setup is very simple and straightforward.
Top Answer: The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
Top Answer: It's the first software that I've used in terms of machine learning. Therefore, I don't have anything to compare it to, however, it was okay for me. I didn't have any problems or anything. Maybe it… more »
Ranking
8th
Views
7,587
Comparisons
6,039
Reviews
5
Average Words per Review
501
Rating
8.4
4th
Views
15,708
Comparisons
12,425
Reviews
16
Average Words per Review
524
Rating
7.7
Comparisons
Also Known As
SPSS Modeler
Azure Machine Learning, MS Azure Machine Learning Studio
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Overview

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
https://www.ibm.com/products/spss-modeler/pricing
 
Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947


Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.

Offer
Learn more about IBM SPSS Modeler
Learn more about Microsoft Azure Machine Learning Studio
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 Turkey
Walgreens Boots Alliance, Schneider Electric, BP
Top Industries
REVIEWERS
University23%
Financial Services Firm15%
Manufacturing Company12%
Government12%
VISITORS READING REVIEWS
Comms Service Provider24%
Computer Software Company18%
Educational Organization8%
Government7%
REVIEWERS
Financial Services Firm14%
Recruiting/Hr Firm14%
Computer Software Company14%
Energy/Utilities Company14%
VISITORS READING REVIEWS
Computer Software Company25%
Comms Service Provider18%
Manufacturing Company6%
Energy/Utilities Company6%
Company Size
REVIEWERS
Small Business24%
Midsize Enterprise6%
Large Enterprise71%
REVIEWERS
Small Business32%
Midsize Enterprise11%
Large Enterprise58%
Find out what your peers are saying about IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: September 2021.
534,468 professionals have used our research since 2012.

IBM SPSS Modeler is ranked 8th in Data Science Platforms with 5 reviews while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 16 reviews. IBM SPSS Modeler is rated 8.4, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM SPSS Modeler writes "User-friendly, and it gives you a lot of visibility through features like comparing fiscal quarters". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". IBM SPSS Modeler is most compared with IBM SPSS Statistics, IBM Watson Studio, KNIME, Alteryx and Weka, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, IBM Watson Studio, Dataiku Data Science Studio, Alteryx and SAS Visual Analytics. See our IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio report.

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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.