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Most Helpful Review
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Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"The Cloudera Data Science Workbench is customizable and easy to use."

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"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure.""The most valuable feature is data normalization.""The UI is very user-friendly and that AI is easy to use.""The solution is very fast and simple for a data science solution.""Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills.""The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.""The AutoML is helpful when you're starting to explore the problem that you're trying to solve.""The interface is very intuitive."

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Cons
"Running this solution requires a minimum of 12GB to 16GB of RAM."

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"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice.""The data cleaning functionality is something that could be better and needs to be improved.""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.""The solution should be more customizable. There should be more algorithms.""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.""Integration with social media would be a valuable enhancement.""The AutoML feature is very basic and they should improve it by using a more robust algorithm.""The data preparation capabilities need to be improved."

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Pricing and Cost Advice
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"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly.""From a developer's perspective, I find the price of this solution high.""The licensing cost is very cheap. It's less than $50 a month."

More Microsoft Azure Machine Learning Studio Pricing and Cost Advice »

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Questions from the Community
Top Answer: The Cloudera Data Science Workbench is customizable and easy to use.
Top Answer: Running this solution requires a minimum of 12GB to 16GB of RAM. In the future, I would like to see a student version of the Data Science Workbench that includes sample datasets that can be used for… more »
Top Answer: I am a professor and this is one of the solutions that I use as a teaching tool for my students. The most recent version can be used by the students while they are working in the labs because our… more »
Top Answer: It's good for citizen data scientists, but also, other people can use Python or .NET code.
Top Answer: The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
Top Answer: Every tool requires some improvement. They have already improved many things. They had added new features and a new pipeline. They should have an on-premise version, other than Python and R Studio… more »
Ranking
18th
Views
4,112
Comparisons
3,615
Reviews
1
Average Words per Review
302
Rating
8.0
4th
Views
14,561
Comparisons
11,621
Reviews
12
Average Words per Review
559
Rating
7.7
Popular Comparisons
Also Known As
CDSW
Azure Machine Learning
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Overview

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. Access any data anywhere – from cloud object storage to data warehouses, CDSW provides connectivity not only to CDH but the systems your data science teams rely on for analysis.

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.

Offer
Learn more about Cloudera Data Science Workbench
Learn more about Microsoft Azure Machine Learning Studio
Sample Customers
IQVIA, Rush University Medical Center, Western Union
Walgreens Boots Alliance, Schneider Electric, BP
Top Industries
VISITORS READING REVIEWS
Computer Software Company31%
Comms Service Provider14%
Financial Services Firm12%
Insurance Company6%
VISITORS READING REVIEWS
Computer Software Company27%
Comms Service Provider19%
Energy/Utilities Company6%
Manufacturing Company6%
Company Size
No Data Available
REVIEWERS
Small Business40%
Midsize Enterprise7%
Large Enterprise53%
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: March 2021.
474,038 professionals have used our research since 2012.

Cloudera Data Science Workbench is ranked 18th in Data Science Platforms with 1 review while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 12 reviews. Cloudera Data Science Workbench is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Cloudera Data Science Workbench writes "Customizable, easy to install, and easy to use". 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". Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Alteryx, Anaconda and KNIME, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Alteryx, IBM Watson Studio, Amazon SageMaker and Dataiku Data Science Studio.

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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.