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Cloudera Data Science Workbench vs Microsoft Azure Machine Learning Studio comparison

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June 2022
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  • "The licensing cost is very cheap. It's less than $50 a month."
  • "There is a license required for this solution."
  • "I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
  • More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →

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    Top Answer:Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
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    Also Known As
    CDSW
    Azure Machine Learning, MS Azure Machine Learning Studio
    Learn More
    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.

    Microsoft Azure Machine Learning Will Help You:

    • Rapidly build and train models
    • Operationalize at scale
    • Deliver responsible solutions
    • Innovate on a more secure hybrid platform

    With Microsoft Azure Machine Learning You Can:

    • Prepare data: Microsoft Azure Machine Learning Studio offers data labeling, data preparation, and datasets.
    • Build and train models: Includes notebooks, Visual Studio Code and Github, Automated ML, Compute instance, a drag-and-drop designer, open-source libraries and frameworks, customizable dashboards, and experiments
    • Validate and deploy: Manage endpoints, automate machine learning workflows (pipeline CI/CD), optimize models, access pre-built container images, share and track models and data, train and deploy models across multi-cloud and on-premises.
    • Manage and monitor: Track, log, and analyze data, models, and resources; Detect drift and maintain model accuracy; Trace ML artifacts for compliance; Apply quota management and automatic shutdown; Leverage built-in and custom policies for compliance management; Utilize continuous monitoring with Azure Security Center.

    Microsoft Azure Machine Learning Features:

    • Easy & flexible building interface: Execute your machine learning development through the Microsoft Azure Machine Learning Studio using drag-and-drop components that minimize the code development and straightforward configuration of properties. By being so flexible, the solution also helps build, test ,and generate advanced analytics based on the data.
    • Wide range of supported algorithms: Configuration is simple and easy because Microsoft Azure ML offers readily available well-known algorithms. There is also no limit in importing training data, and the solution enables you to fine-tune your data easily, saving money and time and helping you generate more revenue.
    • Easy implementation of web services: Simply drag and drop your data sets and algorithms, and link them together to implement web services. It only requires one click to create and publish the web service, which can be used from any device by passing valid credentials.
    • Great documentation: Microsoft Azure provides full stacks of documentation, such as tutorials, quick starts, references, and many other resources that help you understand how to easily build, manage, deploy, and access machine learning solutions effectively.

    Microsoft Azure Machine Learning Benefits:

    • It is fully integrated with Python and R SDKs.
    • It has an updated drag-and-drop interface, generally known as Azure Machine Learning Designer.
    • It supports MLPipelines, where you can build flexible and modular pipelines to automate workflows.
    • It supports multiple model formats depending upon the job type.
    • It has automated model training and hyperparameter tuning with code-first and no-code options.
    • It supports data labeling projects.

    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

    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 Company22%
    Financial Services Firm20%
    Comms Service Provider12%
    Energy/Utilities Company7%
    REVIEWERS
    Financial Services Firm18%
    Recruiting/Hr Firm9%
    Computer Software Company9%
    Energy/Utilities Company9%
    VISITORS READING REVIEWS
    Computer Software Company22%
    Comms Service Provider16%
    Financial Services Firm7%
    Manufacturing Company7%
    Company Size
    VISITORS READING REVIEWS
    Small Business10%
    Midsize Enterprise13%
    Large Enterprise76%
    REVIEWERS
    Small Business28%
    Midsize Enterprise12%
    Large Enterprise60%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise15%
    Large Enterprise68%
    Buyer's Guide
    Data Science Platforms
    June 2022
    Find out what your peers are saying about Databricks, Alteryx, Knime and others in Data Science Platforms. Updated: June 2022.
    610,229 professionals have used our research since 2012.

    Cloudera Data Science Workbench is ranked 15th in Data Science Platforms while Microsoft Azure Machine Learning Studio is ranked 4th in Data Science Platforms with 13 reviews. Cloudera Data Science Workbench is rated 0.0, while Microsoft Azure Machine Learning Studio is rated 7.8. 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". Cloudera Data Science Workbench is most compared with Databricks, Anaconda, Dataiku Data Science Studio, Amazon SageMaker and Google Cloud Datalab, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, IBM Watson Studio and IBM SPSS Statistics.

    See our list of best Data Science Platforms vendors.

    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.