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."In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"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."
"Microsoft Azure Machine Learning Studio is easy to use and deploy."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"It's a great option if you are fairly new and don't want to write too much code."
"The most valuable feature is data normalization."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"The most valuable feature is the ease of setting up visualizations."
"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."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"The most valuable feature is the performance."
"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."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this."
"The solution should be more customizable. There should be more algorithms."
"They should have a desktop version to work on the platform."
"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."
"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."
"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."
"The scripting for customization could be improved."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 48 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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