

What is SAS Visual Data Mining and Machine Learning?
Solve the most complex analytical problems with a single, integrated, collaborative solution – now with its own automated modeling API.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
79 Likeliness to Recommend
91 Plan to Renew
4
Since last award
75 Satisfaction of Cost Relative to Value
2
Since last award
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+93 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love SAS Visual Data Mining and Machine Learning?
Pros
- Helps Innovate
- Enables Productivity
- Trustworthy
- Efficient Service
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Data Cleansing
Data Integration
Data Access
Data Enrichment
Data Modelling Tools
Data Connectors and Data Mashup
Data Packaging
Data Profiling
Cataloging
Data Security
Data Mining
Vendor Capability Ratings
Quality of Features
Ease of Implementation
Ease of IT Administration
Business Value Created
Ease of Customization
Product Strategy and Rate of Improvement
Breadth of Features
Availability and Quality of Training
Usability and Intuitiveness
Ease of Data Integration
Vendor Support
SAS Visual Data Mining and Machine Learning Reviews

Nwoye M.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted May 2025
Powerful Yet Complex.
Likeliness to Recommend
What differentiates SAS Visual Data Mining and Machine Learning from other similar products?
End-to-End Platform: SAS VDMML provides a fully integrated environment for the entire machine learning lifecycle—from data preparation to model deployment—without switching between multiple tools. AutoML and Model Interpretability: VDMML includes robust AutoML capabilities that automate the model-building process, while also offering interpretability tools like partial dependency plots and SHAP (SHapley Additive exPlanations) values to understand model behavior.
What is your favorite aspect of this product?
If I were to highlight the most impactful aspect of SAS Visual Data Mining and Machine Learning (VDMML), it would be its seamless integration of advanced analytics and interpretability within an enterprise-ready environment.
What do you dislike most about this product?
The main drawback of SAS Visual Data Mining and Machine Learning (VDMML) is its steep learning curve and interface complexity, especially for users who are not already familiar with SAS's ecosystem. Unlike more modern, streamlined platforms like DataRobot or Azure ML, VDMML's interface can feel cluttered and overwhelming, requiring substantial training to navigate effectively.
What recommendations would you give to someone considering this product?
Understand Your Use Case: SAS VDMML excels in enterprise-scale analytics, regulated industries (like finance and healthcare), and scenarios needing strong data governance. If your projects require interpretability, large-scale processing, or robust security, it's a solid choice. Evaluate Cost vs. Value: SAS is premium-priced. Ensure the value it brings—like advanced analytics, governance, and scalability—justifies the cost compared to alternatives like Azure ML, DataRobot, or AWS SageMaker.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
Please tell us why you think this review should be flagged.

Damilola A.
- Role: Operations
- Industry: Technology
- Involvement: End User of Application
Submitted Apr 2025
Powerful Tool for Advanced Analytics
Likeliness to Recommend
What differentiates SAS Visual Data Mining and Machine Learning from other similar products?
SAS Visual Data Mining and Machine Learning stands out due to its strong focus on both automation and user experience. It offers an intuitive visual interface that allows users to build, validate, and deploy models without extensive coding knowledge, making it accessible to both data scientists and business analysts. Additionally, SAS's robust data management capabilities seamlessly integrate with the analytics process, ensuring high data quality. The platform also includes advanced algorithms and machine learning techniques, supported by SAS's long-standing expertise in analytics.
What is your favorite aspect of this product?
One of my favourite features of SAS Visual Data Mining and Machine Learning is its user-friendly UI. It simplifies difficult analytics, allowing both experienced data professionals and amateurs to visualise data and construct models without becoming bogged down in coding. I really like how it blends strong algorithms with built-in automation to accelerate the modelling process while maintaining accuracy. It truly allows users to examine their data creatively and make informed conclusions swiftly.
What do you dislike most about this product?
One aspect of SAS Visual Data Mining and Machine Learning that I find frustrating is that the licensing and pricing can be expensive, particularly for smaller organisations or individual users. This may make it less accessible than some other tools on the market. Additionally, while the interface is generally user-friendly, there can still be a learning curve, especially for those who are completely new to data science. It would be great to see more resources or tutorials to help ease that transition.
What recommendations would you give to someone considering this product?
If you're thinking about using SAS Visual Data Mining and Machine Learning, my first suggestion is to try the trial version, if it's available. It's an excellent method to test the features and determine whether they match your specific requirements before making a complete commitment. Invest some time in SAS's training resources and documentation. They provide a multitude of lessons and support to help you flatten the learning curve and get the most out of the product.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
Please tell us why you think this review should be flagged.

Favour J.
- Role: Information Technology
- Industry: Technology
- Involvement: End User of Application
Submitted Feb 2025
Fantastic advanced analytical features
Likeliness to Recommend
What differentiates SAS Visual Data Mining and Machine Learning from other similar products?
Visual Interface that records the entire analytical life cycle process
What is your favorite aspect of this product?
Data Wrangling features
What do you dislike most about this product?
A bit technical
What recommendations would you give to someone considering this product?
Highly Recommended for advanced data analytics
Pros
- Saves Time
- Performance Enhancing
- Enables Productivity
- Trustworthy
Please tell us why you think this review should be flagged.
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