Looking to implement or upgrade SAS Visual Data Mining and Machine Learning?
Schedule a Meeting
Machine Learning

SAS Visual Data Mining and Machine Learning

Accelerate machine learning delivery with visual workflows and advanced analytics

Schedule a Meeting
Category
Software
Ideal For
Data Scientists
Deployment
Cloud / On-premise / Hybrid
Integrations
None+ Apps
Security
Role-based access control, data encryption, audit logging, enterprise authentication
API Access
Yes - comprehensive API for integration and automation

About SAS Visual Data Mining and Machine Learning

SAS Visual Data Mining and Machine Learning is an enterprise-grade platform designed to democratize machine learning across organizations. It combines intuitive visual workflows with advanced programming capabilities, enabling data scientists and business analysts to build, train, and deploy predictive models without extensive coding expertise. The platform accelerates the entire machine learning lifecycle—from data preparation and exploration to model development, validation, and deployment—supporting both supervised and unsupervised learning algorithms. AiDOOS enhances this solution by providing streamlined access to SAS expertise, enabling organizations to optimize platform deployment, accelerate model governance implementation, and integrate seamlessly with existing enterprise data ecosystems. Through AiDOOS, teams gain scalable access to specialized resources for managing complex ML pipelines, ensuring production-ready models, and maximizing return on their SAS investment. The platform's collaborative environment facilitates cross-functional teamwork, allowing stakeholders to translate data insights into actionable business decisions at scale.

Challenges It Solves

  • Complex ML lifecycle slows time-to-insight and model deployment
  • Data scientists spend excessive time on repetitive data preparation tasks
  • Non-technical stakeholders struggle to understand and validate ML models
  • Organizations lack governance frameworks for responsible AI deployment
  • Integration with legacy systems creates bottlenecks in ML pipelines

Proven Results

64
Faster model development and deployment timelines
48
Reduced time spent on data preparation workflows
35
Improved collaboration between technical and business teams

Key Features

Core capabilities at a glance

Visual Model Builder

Drag-and-drop interface for building ML models without coding

Reduce model development time by 50% or more

Automated Data Preparation

Intelligent data cleaning, transformation, and feature engineering

Cut data prep time from weeks to days

Advanced Analytics Engine

Comprehensive algorithms for regression, classification, clustering, and time series

Deploy production-ready models with high accuracy

Model Governance & Monitoring

Track model performance, bias, and compliance in real-time

Ensure responsible AI and regulatory adherence

Interactive Visualizations

Explore data patterns and model insights through dynamic dashboards

Enable stakeholders to validate and trust model decisions

Integration Hub

Connect with enterprise data sources and cloud platforms seamlessly

Reduce integration complexity and deployment friction

Ready to implement SAS Visual Data Mining and Machine Learning for your organization?

Schedule a Meeting

Real-World Use Cases

See how organizations drive results

Predictive Maintenance
Organizations use SAS VDMML to build models predicting equipment failures, reducing downtime and maintenance costs while optimizing asset lifecycle management.
72
40% reduction in unplanned equipment downtime
Customer Churn Prevention
Identify at-risk customers and intervene with targeted retention strategies using advanced segmentation and predictive scoring models.
58
Improve customer retention by 25-30%
Fraud Detection
Deploy real-time anomaly detection models to identify fraudulent transactions and activities, protecting revenue and reducing financial losses.
81
Detect 85% of fraud cases with minimal false positives
Demand Forecasting
Leverage time series and ensemble models to forecast demand accurately, optimizing inventory management and supply chain operations.
66
Improve forecast accuracy by 20-35%
Credit Risk Assessment
Build scoring models to evaluate creditworthiness and loan default probability, enabling faster approvals and risk-adjusted pricing.
53
Increase loan approval processing by 45%

Integrations

Seamlessly connect with your tech ecosystem

A

Apache Spark

Explore

Native integration for distributed processing of large-scale data and model training

S

Salesforce

Explore

Embed predictive models and scores directly into CRM workflows for customer intelligence

T

Tableau

Explore

Visualize model results and insights through powerful business intelligence dashboards

S

Snowflake

Explore

Direct connectivity to cloud data warehouse for seamless data access and processing

A

AWS

Explore

Cloud deployment and integration with AWS services for scalable ML infrastructure

P

Python & R

Explore

Open programming interfaces for advanced users and custom algorithm development

M

Microsoft Azure

Explore

Hybrid deployment option with Azure integration for enterprise cloud strategies

R

REST APIs

Explore

Custom integration endpoints for embedding models into enterprise applications

Implementation with AiDOOS

Outcome-based delivery with expert support

Outcome-Based

Pay for results, not hours

Milestone-Driven

Clear deliverables at each phase

Expert Network

Access to certified specialists

Implementation Timeline

1
Discover
Requirements & assessment
2
Integrate
Setup & data migration
3
Validate
Testing & security audit
4
Rollout
Deployment & training
5
Optimize
Performance tuning

See how it works for your team

Schedule a Meeting

Alternatives & Comparisons

Find the right fit for your needs

Capability SAS Visual Data Mining and Machine Learning Supervisely Checksub ArtificialStudio
Customization Excellent Excellent Good Good
Ease of Use Excellent Good Excellent Excellent
Enterprise Features Excellent Excellent Good Good
Pricing Fair Fair Fair Fair
Integration Ecosystem Excellent Good Good Good
Mobile Experience Good Fair Fair Fair
AI & Analytics Excellent Excellent Excellent Excellent
Quick Setup Good Good Excellent Excellent

Similar Products

Explore related solutions

Supervisely

Supervisely

Supervisely Enterprise Deployment | Secure Annotation Platform Powered by AiDOOS Deploy Supervisely…

Explore
Checksub

Checksub

Automate and Elevate Your Video Localization with Checksub Checksub revolutionizes the way business…

Explore
ArtificialStudio

ArtificialStudio

Transform Multimedia Creation with 40+ AI Tools Unleash creativity and accelerate content productio…

Explore

Frequently Asked Questions

What programming experience is required to use SAS Visual Data Mining and Machine Learning?
The platform supports both visual workflows for non-technical users and advanced programming through Python and R for data scientists. Users of any skill level can leverage the tool effectively. AiDOOS can help you accelerate adoption with training and specialized resources.
Can SAS VDMML be deployed on-premise and in the cloud?
Yes, SAS VDMML supports on-premise, cloud, and hybrid deployment options including AWS, Azure, and private data centers. This flexibility accommodates diverse enterprise IT strategies and data governance requirements.
How does AiDOOS enhance SAS VDMML implementation?
AiDOOS provides access to SAS-certified experts for deployment optimization, advanced pipeline architecture, model governance setup, and enterprise integration. This accelerates time-to-value and ensures best practices are implemented from day one.
What types of models can be built with this platform?
The platform supports classification, regression, clustering, time series forecasting, anomaly detection, and ensemble models. It includes hundreds of algorithms suitable for diverse business use cases across industries.
How are ML models monitored in production?
Built-in monitoring dashboards track model performance metrics, data drift, prediction accuracy, and fairness indicators in real-time. Automated alerts trigger when models require retraining or intervention.
Is there support for responsible AI and bias mitigation?
Yes, SAS VDMML includes tools for bias detection, fairness assessment, model explainability, and compliance reporting. These features ensure your models meet ethical standards and regulatory requirements like GDPR and fair lending laws.