We performed a comparison between Microsoft Azure Machine Learning Studio and TIBCO Data Science based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
"The interface is very intuitive."
"Auto email and studio are great features."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"The most valuable feature is data normalization."
"I like being able to compare results across different training runs. The hyperparameter tuning function is a valuable feature because it provides the ability to run multiple experiments at the same time and compare results."
"The solution is really scalable."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"The most valuable feature is the performance."
"The most valuable feature is the ease of setting up visualizations."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"I would like to see modules to handle Deep Learning frameworks."
"I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased."
"Using the solution requires some specific learning which can take some time."
"The platform's integration feature could be better."
"In the Machine Learning Studio, particularly the Designer part, which is essentially Azure's demo designer, there is room for improvement. Many customers and users tend to switch to Microsoft Azure Multi-Joiners, which is a more basic version, but they do so internally. One area that could use enhancement is the process of connecting components. Currently, every time you want to connect a component, such as linking it to your storage or an instance like EC2, you have to input your username and password repeatedly. This can be quite cumbersome. Google, for instance, has made it more user-friendly by allowing easy access for connecting services within a workspace. In a workspace, you can set up various resources like storage, a database cluster, machine learning studio, and more. When connecting these services, there's no need to enter your username and password each time, making it a more efficient process. Another aspect to consider is the role of the designer, and they were to integrate a large language model to handle various tasks, it could significantly enhance the overall scalability and usability of the platform."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"I would like the visualization for the map of countries to be more easily configurable."
"The scripting for customization could be improved."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 49 reviews while TIBCO Data Science is ranked 25th in Data Science Platforms. Microsoft Azure Machine Learning Studio is rated 7.6, while TIBCO Data Science is rated 7.6. The top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". On the other hand, the top reviewer of TIBCO Data Science writes "A straightforward initial setup and good reporting but needs better documentation". Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform, whereas TIBCO Data Science is most compared with TIBCO Statistica, MathWorks Matlab, Amazon SageMaker and Dataiku Data Science Studio.
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