Compare IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio
IBM SPSS Statistics is ranked 10th in Data Science Platforms with 4 reviews while Microsoft Azure Machine Learning Studio which is ranked 4th in Data Science Platforms with 5 reviews. IBM SPSS Statistics is rated 6.8, while Microsoft Azure Machine Learning Studio is rated 7.4. The top reviewer of IBM SPSS Statistics writes "Provides a good number of modelling techniques although data visualization is not easy to do". On the other hand, 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, MathWorks Matlab and Weka, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker and Alteryx. See our IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio report.
 |
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 2019. 360,284 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 | |
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. Custom tables and macros: They allow us to create useful reports quickly for a broad audience. in terms of the simplicity, I think the SPSS basic can handle it. | Visualisation, and the possibility of sharing functions are key features. 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. |
Cons | |
Needs more statistical modelling functions. Better documentation on how to use macros. Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement. | Operability with R could be improved. 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. |
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. More affordable training for new staff members. If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer. | 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. |
 Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs. 360,284 professionals have used our research since 2012. | |
Ranking  | |
Views 6,716 Comparisons 3,054 Reviews 4 Average Words per Review 266 Avg. Rating 6.8 | Views 8,442 Comparisons 6,867 Reviews 5 Average Words per Review 353 Avg. Rating 7.4 |
Top Comparisons | |
 Compared 30% of the time.  Compared 11% of the time.  Compared 10% of the time. |  Compared 18% of the time.  Compared 11% of the time.  Compared 11% of the time. |
Also Known As | |
| SPSS Statistics | Azure Machine Learning |
Learn | |
| IBM | Microsoft |
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-TILDA | Information Not Available |
Find out what your peers are saying about IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: July 2019.
360,284 professionals have used our research since 2012.
See also IBM SPSS Statistics Reviews, Microsoft Azure Machine Learning Studio Reviews, and our list of Best Data Science Platforms Companies.
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.
Sign in to see all reviews and comparisons. It's free!
By clicking Sign in with LinkedIn™ you agree to let IT Central Station use your LinkedIn profile
and email address in accordance with our Privacy Policy and agree to the Terms of Service.
- Unlimited access to 28000+ reviews from real users
- Your own page to promote your professional skills
- Networking events and peer-to-peer consultations
Already a member? Sign in.
By registering, you agree to our Terms of Service and Privacy Policy.
- Unlimited access to 28000+ reviews from real users
- Your own page to promote your professional skills
- Networking events and peer-to-peer consultations
Already a member? Sign In.