We performed a comparison between Microsoft Azure Machine Learning Studio and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The initial setup is very simple and straightforward."
"The solution is scalable."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"It's a great option if you are fairly new and don't want to write too much code."
"MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse."
"I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
"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 technical support services are good."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"It's relatively simple to create basic dashboards and reports."
"I believe that the possibilities for exploring data and formulating visual results are quite good because it allows the business analyst to have different perspectives on the data."
"The alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."
"Great for handling complex data models."
"The flexibility of the configuration is valuable to me."
"The initial setup time of the containers to run the experiment is a bit long."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
"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."
"I would like to see modules to handle Deep Learning frameworks."
"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."
"They should have a desktop version to work on the platform."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
"The price could be improved."
"There is a need for coding when it comes to digital reporting which can be intimidating."
"A bit more flexibility in the temperatization will be helpful."
"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."
"I haven't come across any missing features."
"SAS Visual Analytics could be more user-friendly."
"The product is expensive and needs the integration of more languages."
"The licensing ends up being more expensive than other options."
"Colours used on report objects"
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 48 reviews while SAS Visual Analytics is ranked 7th in Data Visualization with 35 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while SAS Visual Analytics is rated 8.0. 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 SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Alteryx, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Dataiku Data Science Studio and SAS Enterprise Miner.
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