Compare IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio

IBM SPSS Statistics is ranked 4th in Data Science Platforms with 12 reviews while Microsoft Azure Machine Learning Studio is ranked 7th in Data Science Platforms with 6 reviews. IBM SPSS Statistics is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.4. 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 "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". IBM SPSS Statistics is most compared with IBM SPSS Modeler, Weka, MathWorks Matlab, TIBCO Statistica and KNIME, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Alteryx, Amazon SageMaker, KNIME and IBM Watson Studio. See our IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio report.
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Most Helpful Review
Find out what your peers are saying about IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: July 2020.
430,585 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 features that I have found most valuable are the Bayesian statistics and descriptive statistics.Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things.The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS.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.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 has the ability to easily change any variable in our research.They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do.

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The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.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 UI is very user-friendly and that AI is easy to use.The most valuable feature is data normalization.The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure.

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Cons
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 would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that.One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated.The solution needs more planning tools and capabilities.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.This solution is not suitable for use with Big Data.The design of the experience can be improved.The product should provide more ways to import data and export results that are user-friendly for high-level executives.

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Integration with social media would be a valuable enhancement.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.The solution should be more customizable. There should be more algorithms.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 cleaning functionality is something that could be better and needs to be improved.If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice.

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Pricing and Cost Advice
The price of this solution is a little bit high, which was a problem for my company.We think that IBM SPSS is expensive for this function.

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From a developer's perspective, I find the price of this solution high.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.

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4th
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3,637
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2,894
Reviews
12
Average Words per Review
714
Avg. Rating
7.9
7th
Views
12,495
Comparisons
10,046
Reviews
6
Average Words per Review
554
Avg. Rating
7.3
Popular Comparisons
Compared 14% of the time.
Compared 4% of the time.
Also Known As
SPSS StatisticsAzure Machine Learning
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Overview
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.

Offer
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-TILDAWalgreens Boots Alliance, Schneider Electric, BP
Top Industries
REVIEWERS
University27%
Financial Services Firm18%
Analyst Firm9%
Consumer Goods Company9%
VISITORS READING REVIEWS
Computer Software Company24%
K 12 Educational Company Or School17%
Comms Service Provider12%
Media Company9%
VISITORS READING REVIEWS
Computer Software Company36%
Comms Service Provider11%
K 12 Educational Company Or School7%
Media Company6%
Find out what your peers are saying about IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: July 2020.
430,585 professionals have used our research since 2012.

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