We changed our name from IT Central Station: Here's why

IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio comparison

You must select at least 2 products to compare!
Featured Review
Find out what your peers are saying about IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2022.
563,327 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:
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions.""The most valuable feature is the user interface because you don't need to write code.""It is a modeling tool with helpful automation.""Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful.""SPSS is quite robust and quicker in terms of providing you the output.""The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful.""You can quickly build models because it does the work for you.""The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."

More IBM SPSS Statistics Pros →

"The most valuable feature is its compatibility with Tensorflow.""It's good for citizen data scientists, but also, other people can use Python or .NET code.""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.""The initial setup is very simple and straightforward.""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.""The solution is very fast and simple for a data science solution.""The AutoML is helpful when you're starting to explore the problem that you're trying to solve."

More Microsoft Azure Machine Learning Studio Pros →

"This solution is not suitable for use with Big Data.""I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better.""Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them.""I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities.""It could provide even more in the way of automation as there are many opportunities.""If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution.""It could allow adding color to data models to make them easier to interpret.""The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."

More IBM SPSS Statistics Cons →

"Integration with social media would be a valuable enhancement.""I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else.""I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system.""The AutoML feature is very basic and they should improve it by using a more robust algorithm.""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.""There should be data access security, a role level security. Right now, they don't offer this.""n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces.""The solution should be more customizable. There should be more algorithms."

More Microsoft Azure Machine Learning Studio Cons →

Pricing and Cost Advice
  • "The price of this solution is a little bit high, which was a problem for my company."
  • "The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
  • More IBM SPSS Statistics 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 →

    Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
    563,327 professionals have used our research since 2012.
    Questions from the Community
    Top Answer: 
    SPSS is quite robust and quicker in terms of providing you the output.
    Top Answer: 
    You can download it for free, but if you want to enable the professional features, you can buy one license if that's all you need. But if you have many collaborators and want to add more contributors… more »
    Top Answer: 
    From an improvement standpoint, I could compare to PyCharm and see how many other things you can automate things. In PyCharm you use Python and have a lot of packages. SPSS is missing out on some of… 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.
    Average Words per Review
    Average Words per Review
    Also Known As
    SPSS Statistics
    Azure Machine Learning, MS Azure Machine Learning Studio
    Learn More
    Your organization has more data than ever, but spreadsheets and basic statistical analysis tools limit its usefulness. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next. Virtually eliminate time-consuming data prep; and quickly create, manipulate and distribute insights for decision making.

    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

    Learn more about IBM SPSS Statistics
    Learn more about Microsoft Azure Machine Learning Studio
    Sample Customers
    LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
    Walgreens Boots Alliance, Schneider Electric, BP
    Top Industries
    Financial Services Firm19%
    Aerospace/Defense Firm6%
    Non Profit6%
    Comms Service Provider25%
    Computer Software Company17%
    Educational Organization13%
    Financial Services Firm14%
    Recruiting/Hr Firm14%
    Computer Software Company14%
    Energy/Utilities Company14%
    Computer Software Company24%
    Comms Service Provider19%
    Energy/Utilities Company6%
    Manufacturing Company6%
    Company Size
    Small Business32%
    Midsize Enterprise23%
    Large Enterprise45%
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    Find out what your peers are saying about IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2022.
    563,327 professionals have used our research since 2012.

    IBM SPSS Statistics is ranked 5th in Data Science Platforms with 13 reviews while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 16 reviews. IBM SPSS Statistics is rated 8.2, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". 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 Statistics is most compared with IBM SPSS Modeler, Weka, Alteryx, TIBCO Statistica and MathWorks Matlab, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Dataiku Data Science Studio, IBM Watson Studio, KNIME and MathWorks Matlab. See our IBM SPSS Statistics 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.