What is better IBM Predictive Analytics or Microsoft Azure Machine Learning Studio? When looking for the ideal Predictive Analysis Software for your organization our recommendation is that you assess the functions, rates, and other crucial info regarding the product and vendor. Here, you can check the parallels and discrepancies between IBM Predictive Analytics (overall score at 9.4 and user satisfaction at 95%) and Microsoft Azure Machine Learning Studio (overall score at 9.6 and user satisfaction at N/A%).
It's also possible to check their unique details, like tools, plans, costs, terms and conditions, etc. What is more, analyze the terms carefully for information on hidden costs, such as, setup fees, independent customer service, upgrade fees, disk space fees, and more.
In case you you want to quickly find the top Predictive Analysis Software according to our review team we suggest you take a look at these products: Wolfram Mathematica, Sisense, Microsoft Azure Machine Learning Studio.
IBM Predictive Analytics offers a detailed enterprise pricing structure that features both quote based and subscription-based pricing. Apart from the IBM SPSS Statistics, all the other products in the suite offer subscription-based pricing.
IBM SPSS Statistics @ $99/month
IBM SPSS Modeler @ quote based
IBM SPSS Analytic Server @ quote based
IBM SPSS Predictive Analytics Enterprise @ quote based
US Open, California Franchise Tax Board, First Tennessee Bank
Available Devices
Windows
Linux
Android
iPhone/iPad
Mac
Web-based
Windows Mobile
Company Size
Small Business
Large Enterprises
Medium Business
Freelancers
Available Support
email
phone
live support
training
tickets
General Info
A flexible and scalable predictive analytics suite designed to address all aspects of the entire analytical process; data collection, planning, deployment, analysis, and reporting.
A cloud-based interactive programming tool for predictive analytics from Microsoft. Azure Machine Learning Studio offers access to Cortana Intelligence Suite and gallery, AI algorithm library, and more. Its easy to use interface utilizes drag and drop actions. Despite being cloud-based, this machine learning solution provides offline access to its users.
In case you continue having second thoughts about which product will work best in your case it might be a sound idea to check out each service’s social metrics. These metrics are usually a way to see how popular a given app is and how wide is its online presence.For instance, if you look at IBM Predictive Analytics LinkedIn profile you’ll learn that they are followed by 43677 people. In case of Microsoft Azure Machine Learning Studio the volume of followers on their LinkedIn page is 10514.
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