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IBM SPSS Modeler vs Microsoft Azure Machine Learning Studio comparison

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Featured Review
Find out what your peers are saying about IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2022.
563,208 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
"The supervised models are valuable. It is also very organized and easy to use.""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.""It is a great product for running statistical analysis.""Automation is great and this product is very organized.""Very good data aggregation."

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"The interface is very intuitive.""The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.""Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon.""It's a great option if you are fairly new and don't want to write too much code.""Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills.""Azure's AutoML feature is probably better than the competition.""The solution is very easy to use, so far as our data scientists are concerned.""The UI is very user-friendly and that AI is easy to use."

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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.""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.""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."

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"They should have a desktop version to work on the platform.""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.""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 data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team.""The interface is a bit overloaded.""n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces.""In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great.""It would be nice if the product offered more accessibility in general."

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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 →

  • "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: 
    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: 
    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… more »
    Top Answer: 
    Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
    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.
    Ranking
    7th
    Views
    7,053
    Comparisons
    5,659
    Reviews
    5
    Average Words per Review
    501
    Rating
    8.4
    4th
    Views
    16,529
    Comparisons
    13,221
    Reviews
    14
    Average Words per Review
    484
    Rating
    7.7
    Comparisons
    Also Known As
    SPSS Modeler
    Azure Machine Learning, MS Azure Machine Learning Studio
    Learn More
    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.

    Microsoft Azure Machine Learning Will Help You:

    • Rapidly build and train models
    • Operationalize at scale
    • Deliver responsible solutions
    • Innovate on a more secure hybrid platform

    With Microsoft Azure Machine Learning You Can:

    • Prepare data: Microsoft Azure Machine Learning Studio offers data labeling, data preparation, and datasets.
    • Build and train models: Includes notebooks, Visual Studio Code and Github, Automated ML, Compute instance, a drag-and-drop designer, open-source libraries and frameworks, customizable dashboards, and experiments
    • Validate and deploy: Manage endpoints, automate machine learning workflows (pipeline CI/CD), optimize models, access pre-built container images, share and track models and data, train and deploy models across multi-cloud and on-premises.
    • Manage and monitor: Track, log, and analyze data, models, and resources; Detect drift and maintain model accuracy; Trace ML artifacts for compliance; Apply quota management and automatic shutdown; Leverage built-in and custom policies for compliance management; Utilize continuous monitoring with Azure Security Center.

    Microsoft Azure Machine Learning Features:

    • Easy & flexible building interface: Execute your machine learning development through the Microsoft Azure Machine Learning Studio using drag-and-drop components that minimize the code development and straightforward configuration of properties. By being so flexible, the solution also helps build, test ,and generate advanced analytics based on the data.
    • Wide range of supported algorithms: Configuration is simple and easy because Microsoft Azure ML offers readily available well-known algorithms. There is also no limit in importing training data, and the solution enables you to fine-tune your data easily, saving money and time and helping you generate more revenue.
    • Easy implementation of web services: Simply drag and drop your data sets and algorithms, and link them together to implement web services. It only requires one click to create and publish the web service, which can be used from any device by passing valid credentials.
    • Great documentation: Microsoft Azure provides full stacks of documentation, such as tutorials, quick starts, references, and many other resources that help you understand how to easily build, manage, deploy, and access machine learning solutions effectively.

    Microsoft Azure Machine Learning Benefits:

    • It is fully integrated with Python and R SDKs.
    • It has an updated drag-and-drop interface, generally known as Azure Machine Learning Designer.
    • It supports MLPipelines, where you can build flexible and modular pipelines to automate workflows.
    • It supports multiple model formats depending upon the job type.
    • It has automated model training and hyperparameter tuning with code-first and no-code options.
    • It supports data labeling projects.

    Reviews from Real Users:

    "The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates

    "The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company

    "The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company

    "The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company

    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 Provider25%
    Computer Software Company19%
    Educational Organization8%
    Government7%
    REVIEWERS
    Financial Services Firm14%
    Recruiting/Hr Firm14%
    Computer Software Company14%
    Energy/Utilities Company14%
    VISITORS READING REVIEWS
    Computer Software Company24%
    Comms Service Provider19%
    Energy/Utilities Company6%
    Manufacturing Company6%
    Company Size
    REVIEWERS
    Small Business24%
    Midsize Enterprise6%
    Large Enterprise71%
    REVIEWERS
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    Find out what your peers are saying about IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2022.
    563,208 professionals have used our research since 2012.

    IBM SPSS Modeler is ranked 7th 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 "Has the ability to do templating and transfer it so that we can do multiple types of models and data mining". IBM SPSS Modeler is most compared with IBM Watson Studio, KNIME, IBM SPSS Statistics, Alteryx and RapidMiner, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Dataiku Data Science Studio, IBM Watson Studio, KNIME and Amazon Comprehend. See our IBM SPSS Modeler vs. Microsoft Azure Machine Learning Studio report.

    See our list of best Data Science Platforms vendors.

    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.