IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio

IBM SPSS Statistics is ranked 7th in Data Science Platforms with 4 reviews vs Microsoft Azure Machine Learning Studio which is ranked 5th in Data Science Platforms with 5 reviews. The top reviewer of IBM SPSS Statistics writes "Provides a good number of modelling techniques although data visualization is not easy to do". The top reviewer of Microsoft Azure Machine Learning Studio writes "Enables quick creation of models for PoC in predictive analysis, but needs better ensemble modeling". IBM SPSS Statistics is most compared with IBM SPSS Modeler, SAS Enterprise Miner and KNIME. Microsoft Azure Machine Learning Studio is most compared with RapidMiner, IBM SPSS Modeler and IBM Data Science Experience. See our IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio report.
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Most Helpful Review
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Quotes From Members Comparing IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pros
It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation.The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis.

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It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component.When you import the dataset you can see the data distribution easily with graphics and statistical measures.Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most.MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse.The graphical nature of the output makes it very easy to create PowerPoint reports as well.Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently.Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing.It helps in building customized models, which are easy for clients to use​.​​

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Cons
Needs more statistical modelling functions.

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I would like to see modules to handle Deep Learning frameworks.I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated.Enable creating ensemble models easier, adding more machine learning algorithms.​It could use to add some more features in data transformation, time series and the text analytics section.Microsoft should also include more examples and tutorials for using this product.​

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Pricing and Cost Advice
Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure.

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To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS.

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Ibm spss statistics vs. microsoft azure machine learning studio report from it central station 2018 05 04 thumbnail
Find out what your peers are saying about IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio and others in Data Science Platforms.
269,925 professionals have used our research since 2012.
Ranking
RANKING
Views
4,617
Comparisons
3,780
Reviews
4
Followers
378
Avg. Rating
6.8
Views
2,274
Comparisons
1,988
Reviews
5
Followers
43
Avg. Rating
7.6
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Also Known As
Also Known AsSPSS StatisticsAzure Machine Learning
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Website/VideoIBM
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Microsoft
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OverviewQuestionmark icon
OverviewYour 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.

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Sample Customers
Sample CustomersLDB 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
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Top Industries
VISITORS READING REVIEWS
Financial Services Firm
18%
University
13%
Pharma/Biotech Company
11%
Retailer
11%
No Data Available
Ibm spss statistics vs. microsoft azure machine learning studio report from it central station 2018 05 04 thumbnail
Find out what your peers are saying about IBM SPSS Statistics vs Microsoft Azure Machine Learning Studio and others in Data Science Platforms.
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269,925 professionals have used our research since 2012.
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