IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio comparison

You must select at least 2 products to compare!
Comparison Buyer's Guide
Executive Summary

We performed a comparison between IBM SPSS Statistics and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio Report (Updated: November 2022).
655,113 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics.""The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful.""You can quickly build models because it does the work for you.""The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial.""SPSS is quite robust and quicker in terms of providing you the output.""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 can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools.""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 →

"Their support is helpful.""The solution is very easy to use, so far as our data scientists are concerned.""What I like best about Microsoft Azure Machine Learning Studio is that it's a straightforward tool and it's easy to use. Another valuable feature of the tool is AutoML which lets you get better metrics to train the model right and with good accuracy. The AutoML feature allows you to simply put in your data, and it'll pre-process and create a more accurate model for you. You don't have to do anything because AutoML in Microsoft Azure Machine Learning Studio will take care of it.""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 good for citizen data scientists, but also, other people can use Python or .NET code.""The most valuable feature is its compatibility with Tensorflow.""Their web interface is good.""Auto email and studio are great features."

More Microsoft Azure Machine Learning Studio Pros →

"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert.""There is a learning curve; it's not very steep, but there is one.""SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer.""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.""I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input.""The solution could improve by providing a visual network for predictions and a self-organizing map for clustering.""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.""SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."

More IBM SPSS Statistics Cons →

"Using the solution requires some specific learning which can take some time.""This solution could be improved if they could integrate the data pipeline scheduling part for their interface.""As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased.""It would be nice if the product offered more accessibility in general.""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.""Technical support could improve their turnaround time.""In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data.""Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."

More Microsoft Azure Machine Learning Studio Cons →

Pricing and Cost Advice
  • "It's quite expensive, but they do a special deal for universities."
  • "The price of IBM SPSS Statistics could improve."
  • "SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
  • 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."
  • "In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting."
  • "My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it."
  • 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.
    655,113 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:I've used SPSS for my doctoral research and in my work as an academic and consultant. It's useful for getting reliable insights into survey data and performing quantitative data analysis. SPSS does… more »
    Top Answer:SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools.
    Top Answer:SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced.
    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

    IBM SPSS Statistics is a cloud-based data analysis engine that can prove to be critical to business intelligence operations. It aims to take large caches of data and make them both useful and meaningful. Users in any field of business can use it to transform their raw data into information that they can easily leverage into solutions for any number of problems. IBM SPSS Statistics uses machine learning algorithms to mine and enrich the data that passes through it.

    IBM SPSS Statistics Benefits

    Some of the ways that organizations can benefit by deploying IBM SPSS Statistics include:

    • Ease of use. IBM SPSS Statistics is simple for users to manipulate and control. The user interface is intuitive and enables users to analyze data without requiring them to have a knowledge of coding.
    • Comprehensive. Instead of requiring users to invest in many different solutions to fulfill different statistics-related tasks, IBM SPSS Statistics enables users to do the work that ordinarily would require multiple solutions.
    • Automation. IBM SPSS Statistics enables users to automate the data analysis process. This means that users do not need to worry that they will miss anomalies or outliers in the data.

    IBM SPSS Statistics Features

    • Predictive analytics. IBM SPSS Statistics gives users the ability to employ machine learning in a way that can help them predict the future. Patterns in the data can be analyzed to see if they can provide them with clues as to how they should approach their future business strategies.
    • Collaboration. The solution offers tools that enable users who are on different teams or in different departments to work together on various aspects of the statistical analysis process.
    • Data discovery. This feature enables users to collect and evaluate their data. These evaluations aid them in finding trends and patterns in their data.
    • Data visualization. These tools enable users to represent their data in visual ways that are easy to understand.

    • Data preparation tools. These features enable organizations to prepare the data for analysis and other measures that will make it useful. One such feature is anomaly detection, which scans for unusual cases in the data.

    Reviews from Real Users

    IBM SPSS Statistics is a solution that stands out when compared to many of its competitors. Two major advantages it offers are the sheer number of functionalities that it puts at a user’s disposal and its user-friendly system interface.

    The director of systems management & MIS operations at a university writes, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it. It's a dashboard where they can get more information. And then, if they want to do a deeper dive into some things, they tell us, and we will work with the research department. We can either add or point to the field or fields and give them some more details.”

    Laurence M., a professor of health services research at a university, writes, “The most valuable feature of IBM SPSS Statistics is all the functionality it provides.”

    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 Firm17%
    Aerospace/Defense Firm6%
    Non Profit6%
    Comms Service Provider21%
    Educational Organization12%
    Computer Software Company10%
    Financial Services Firm15%
    Media Company8%
    Comms Service Provider8%
    Computer Software Company15%
    Comms Service Provider10%
    Financial Services Firm10%
    Manufacturing Company7%
    Company Size
    Small Business36%
    Midsize Enterprise20%
    Large Enterprise44%
    Small Business16%
    Midsize Enterprise16%
    Large Enterprise69%
    Small Business28%
    Midsize Enterprise10%
    Large Enterprise62%
    Small Business16%
    Midsize Enterprise13%
    Large Enterprise71%
    Buyer's Guide
    IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio
    November 2022
    Find out what your peers are saying about IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: November 2022.
    655,113 professionals have used our research since 2012.

    IBM SPSS Statistics is ranked 5th in Data Science Platforms with 10 reviews while Microsoft Azure Machine Learning Studio is ranked 3rd in Data Science Platforms with 15 reviews. IBM SPSS Statistics is rated 8.6, 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 a drag and drop feature and easier learning curve, but the number of algorithms available could still be improved". IBM SPSS Statistics is most compared with IBM SPSS Modeler, Alteryx, Weka, TIBCO Statistica and Oracle Advanced Analytics, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker, TensorFlow, Dataiku Data Science Studio and 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.