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Microsoft Azure Machine Learning Studio vs SAS Visual Analytics comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between Microsoft Azure Machine Learning Studio and SAS Visual Analytics 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.

To learn more, read our detailed Microsoft Azure Machine Learning Studio vs. SAS Visual Analytics report (Updated: September 2022).
633,572 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It's good for citizen data scientists, but also, other people can use Python or .NET code.""The initial setup is very simple and straightforward.""What I like best about Microsoft Azure Machine Learning Studio is that it's a straightforward tool and it's easy to use. Another valuable feature of the tool is AutoML which lets you get better metrics to train the model right and with good accuracy. The AutoML feature allows you to simply put in your data, and it'll pre-process and create a more accurate model for you. You don't have to do anything because AutoML in Microsoft Azure Machine Learning Studio will take care of it.""The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps.""Auto email and studio are great features.""Azure's AutoML feature is probably better than the competition.""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.""Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."

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"We've found the product to be stable and reliable.""It's quite easy to learn and to progress with SAS from an end-user perspective.""It provided the capability to visualize a bunch of data in an organized way.""It's a stable, reliable product.""Great for handling complex data models.""It's relatively simple to create basic dashboards and reports.""Data handling is one of the best features of SAS Visual Analytics.""It integrates well with SAS, making it simple and quick for developers."

More SAS Visual Analytics Pros →

Cons
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces.""There should be data access security, a role level security. Right now, they don't offer this.""Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me.""Using the solution requires some specific learning which can take some time.""In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data.""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.""Technical support could improve their turnaround time.""They should have a desktop version to work on the platform."

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"There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else.""In Brazil, there are few documents, courses, and other resources for studying and implementing the tool.""The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy.""The solution is a little weak at the front end.""There is a need for coding when it comes to digital reporting which can be intimidating.""The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive.""The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good.""The installation process can be a bit complex."

More SAS Visual Analytics Cons →

Pricing and Cost Advice
  • "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."
  • "In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting."
  • "My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it."
  • More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →

  • "$10,000 per annum for an enterprise license."
  • "The cost of the solution can be expensive. There is an additional cost for users."
  • "Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
  • "SAS Visual Analytics is expensive, as is the rest of the platform."
  • "It's approximately $114,000 US dollars per year."
  • "It was licensed for corporate use, and its licensing was on a yearly basis."
  • More SAS Visual Analytics Pricing and Cost Advice →

    report
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    Questions from the Community
    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 »
    Top Answer:The initial setup is very simple and straightforward.
    Top Answer:The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
    Top Answer:Great for handling complex data models.
    Top Answer:I don't directly deal with licensing. I can't speak to the exact price of the product.
    Top Answer:The solution is a little weak at the front end.
    Ranking
    3rd
    Views
    20,159
    Comparisons
    16,748
    Reviews
    16
    Average Words per Review
    513
    Rating
    7.6
    4th
    out of 58 in Data Visualization
    Views
    8,565
    Comparisons
    6,894
    Reviews
    13
    Average Words per Review
    550
    Rating
    8.3
    Comparisons
    Also Known As
    Azure Machine Learning, MS Azure Machine Learning Studio
    SAS BI
    Learn More
    Overview

    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

    SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.

    SAS Visual Analytics Features

    SAS Visual Analytics has many valuable key features. Some of the most useful ones include:

    • Data
    • Interactive data discovery
    • Augmented analytics
    • Chat-enabled analytics
    • Sharing and collaboration
    • Visual analytics apps
    • Embedded insights
    • Location analytics
    • Security and administration
    • In-memory engine

    SAS Visual Analytics Benefits

    There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:

    • Machine learning and natural language: SAS Visual Analytics uses machine learning and natural language explanations to find, visualize, and narrate stories and insights that are easy to understand and explain. This enables you to find out why something happened, examine all options, and uncover opportunities hidden deep in your data.
    • Easy and efficient reporting: With SAS Visual Analytics, you can create interactive reports and dashboards so you can quickly summarize key performance metrics and share them via the web and mobile devices.
    • Easy to use: SAS Visual Analytics was designed to be easy to use. Its easy-to-use predictive analytics enables even business analysts to assess possible outcomes, which also helps organizations make smarter, data-driven decisions.
    • Self-service data: Self-service data preparation gives users the ability to import their own data, join tables, create calculated columns, apply data quality functions, and more. In turn, the solution empowers users to access, combine, clean, and prepare their own data in an agile way, which helps facilitate faster, broader adoption of analytics for your entire organization.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.

    A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.

    PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “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.

    Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”

    Offer
    Learn more about Microsoft Azure Machine Learning Studio
    Learn more about SAS Visual Analytics
    Sample Customers
    Walgreens Boots Alliance, Schneider Electric, BP
    Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
    Top Industries
    REVIEWERS
    Financial Services Firm15%
    Recruiting/Hr Firm8%
    Computer Software Company8%
    Energy/Utilities Company8%
    VISITORS READING REVIEWS
    Computer Software Company16%
    Comms Service Provider12%
    Financial Services Firm9%
    Manufacturing Company7%
    REVIEWERS
    Insurance Company19%
    Financial Services Firm19%
    Government13%
    Transportation Company6%
    VISITORS READING REVIEWS
    Computer Software Company17%
    Financial Services Firm14%
    Government11%
    Comms Service Provider10%
    Company Size
    REVIEWERS
    Small Business28%
    Midsize Enterprise10%
    Large Enterprise62%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise14%
    Large Enterprise70%
    REVIEWERS
    Small Business32%
    Midsize Enterprise23%
    Large Enterprise45%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise11%
    Large Enterprise72%
    Buyer's Guide
    Data Science Platforms
    September 2022
    Find out what your peers are saying about Databricks, Alteryx, Microsoft and others in Data Science Platforms. Updated: September 2022.
    633,572 professionals have used our research since 2012.

    Microsoft Azure Machine Learning Studio is ranked 3rd in Data Science Platforms with 19 reviews while SAS Visual Analytics is ranked 4th in Data Visualization with 13 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while SAS Visual Analytics is rated 8.4. The top reviewer of Microsoft Azure Machine Learning Studio writes "Has a drag and drop feature and easier learning curve, but the number of algorithms available could still be improved". On the other hand, the top reviewer of SAS Visual Analytics writes "Easy to learn and use with good scalability potential". Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, IBM Watson Studio and IBM SPSS Statistics, whereas SAS Visual Analytics is most compared with Tableau, Microsoft BI, Databricks, Qlik Sense and SAS Enterprise Miner.

    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.