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."The most valuable feature is the user interface because you don't need to write code."
"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."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"The most valuable feature is its robust statistical analysis capabilities."
"IBM SPSS Statistics depends on AI."
"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 features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"It is a modeling tool with helpful automation."
"The initial setup is very simple and straightforward."
"Auto email and studio are great features."
"The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"The product is well organized. The thing is how we will get the models to work within our code. We have some suggestions there, but we want to gain more experience and be ready to answer that because we are currently working on this and don't have all the answers yet. The tool is well organized. What I am very happy about is the ease of deploying new resources. You can easily create your pipeline within minutes."
"Their web interface is good."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"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."
"I think the visualization and charting should be changed and made easier and more effective."
"The technical support should be improved."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"The solution needs to improve forecasting using time series analysis."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"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."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"This solution is not suitable for use with Big Data."
"Integration with social media would be a valuable enhancement."
"The data cleaning functionality is something that could be better and needs to be improved."
"One problem I experience is that switching between multiple accounts can be difficult. I don't think there are any major issues. Mostly, the biggest challenge is to identify business solutions to this. The tool should keep on updating new algorithms and not stay static."
"The price of the solution has room for improvement."
"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."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"In terms of data capabilities, if we compare it to Google Cloud's BigQuery, we find a difference. When fetching data from web traffic, Google can do a lot of processing with small queries or functions."
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IBM SPSS Statistics is ranked 7th in Data Science Platforms with 36 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews. IBM SPSS Statistics is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". 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 Alteryx, TIBCO Statistica, Weka, IBM SPSS Modeler and Oracle Advanced Analytics, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and SAS Visual Analytics. See our IBM SPSS Statistics vs. Microsoft Azure Machine Learning Studio report.
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