"Ability to work collaboratively without having to worry about the infrastructure."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"The initial setup is pretty easy."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"The fast data loading process and data storage capabilities are great."
"It's easy to increase performance as required."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"The solution is very easy to use, so far as our data scientists are concerned."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"The interface is very intuitive."
"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."
"It's a great option if you are fairly new and don't want to write too much code."
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."
"The most valuable feature is its compatibility with Tensorflow."
"Anyone who doesn't know SQL may find the product difficult to work with."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"The integration of data could be a bit better."
"Pricing is one of the things that could be improved."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"There are no direct connectors — they are very limited."
"A lot of people are required to manage this solution."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"It would be nice if the product offered more accessibility in general."
"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."
"They should have a desktop version to work on the platform."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"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."
"There should be data access security, a role level security. Right now, they don't offer this."
"The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team."
"I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system."
Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.
Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.
Microsoft Azure Machine Learning Will Help You:
With Microsoft Azure Machine Learning You Can:
Microsoft Azure Machine Learning Features:
Microsoft Azure Machine Learning Benefits:
Reviews from Real Users:
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company
"The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company
"The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company
Databricks is ranked 2nd in Data Science Platforms with 22 reviews while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 16 reviews. Databricks is rated 7.8, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Has the ability to do templating and transfer it so that we can do multiple types of models and data mining". Databricks is most compared with Amazon SageMaker, Azure Stream Analytics, Alteryx, Dataiku Data Science Studio and Google Cloud Datalab, whereas Microsoft Azure Machine Learning Studio is most compared with Dataiku Data Science Studio, IBM Watson Studio, KNIME, Alteryx and Amazon SageMaker. See our Databricks vs. Microsoft Azure Machine Learning Studio report.
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We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.