We performed a comparison between Alteryx 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 feature that I have found most valuable for Alteryx is its geo-referencing feature, it is very good. I use it a lot, especially for supply chain."
"The ease-of-use allows non-technical business users to directly create their own solutions without the use of additional development resources."
"The most valuable feature of Alteryx is the intelligence suite."
"Alteryx has a good UI. We use it frequently in our projects. The tool comes with drag-and-drop features and is easy to understand for business needs. One situation where Alteryx's advanced analytics capabilities were particularly beneficial for us was during a forecasting project. Unlike Python, which requires coding, Alteryx simplifies the process significantly. With Alteryx, users can adjust parameters within the user interface without writing any code."
"The three data signs and data engineering are great features."
"Its initial setup is easy."
"The solution has a very strong community that is involved in the product. It helps make the usage easier and helps us find answers to our questions."
"The data transformation feature is the most valuable. The ability to ingest data, visualize data, and transform that data is useful."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"The solution is very easy to use, so far as our data scientists are concerned."
"Visualisation, and the possibility of sharing functions are key features."
"The solution's most beneficial feature is its integration with Azure."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"Their web interface is good."
"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."
"ML Studio is very easy to maintain."
"There have been some issues with licensing, particularly with the increased prices. This has led some companies, including ours, to consider reducing the number of licenses or potentially discontinuing their use of Alteryx."
"Mastering Alteryx, a comprehensive solution, takes time. However, once you have gained proficiency with its layout and how to drag, drop, and connect components, it becomes remarkably easy, yet still thorough."
"It would be great to create the final users' visualization within Alteryx."
"The solution could improve in the visualization."
"It seems to me that it is not always user friendly."
"They should make the solution user-friendly for nontechnical people by giving specific names to the options."
"It would be great if Alteryx could take third party tools and incorporate them."
"We can't browse multiple files. When we deploy a solution on a gallery, let's say I have ten different files, and I have to upload them all at once. This is something that's difficult in the gallery. So case by case, I see some downsides, but often we do something alternative."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"I would like to see modules to handle Deep Learning frameworks."
"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."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"There should be data access security, a role level security. Right now, they don't offer this."
"The solution should be more customizable. There should be more algorithms."
"Stability-wise, you may face certain problems when you fail to refresh the data in the solution."
"A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer."
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Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 50 reviews. Alteryx is rated 8.4, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". 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". Alteryx is most compared with KNIME, Databricks, Dataiku Data Science Studio, RapidMiner and Starburst Enterprise, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and RapidMiner. See our Alteryx vs. Microsoft Azure Machine Learning Studio report.
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