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Description
Oracle Data Miner empowers data scientists, "citizen data scientists," along with business and data analysts to interact seamlessly with data within the database through an intuitive graphical interface that utilizes a "drag and drop" workflow editor. As an extension of Oracle SQL Developer, Oracle Data Miner (ODMr) effectively captures and visually documents the analytical processes users follow while delving into data and crafting machine learning techniques. The workflows created with ODMr are instrumental for not only re-executing analytical methods but also for facilitating knowledge sharing among team members. Moreover, ODMr efficiently produces SQL and PL/SQL scripts while providing a workflow API that streamlines the deployment of models across the organization. By minimizing data movement, ensuring scalability for big data, maintaining security, and speeding up the transition from model development to deployment, organizations can effectively harness their data assets. This enhanced approach ultimately leads to more informed decision-making and improved business outcomes.
Description
SAS Viya is an advanced cloud-native data and AI platform designed to help organizations manage data, develop AI models, and operationalize analytics from one unified environment. The platform combines data access, machine learning, analytics, governance, and decision deployment into a scalable system built for enterprise use. SAS Viya enables businesses to connect to data across multiple sources while maintaining transparency, lineage, governance, and auditability throughout the AI lifecycle. Organizations can use the platform to accelerate model development, streamline workflows, and deploy trusted AI solutions faster and more efficiently. The platform includes built-in governance features that support fairness, explainability, compliance, and responsible AI practices across teams and business processes. SAS Viya also supports secure AI agent integration through the SAS Viya MCP Server, allowing AI-driven tools and copilots to interact with enterprise workflows responsibly. Businesses can deploy the platform in cloud, hybrid, or on-premises environments based on operational and security requirements. SAS Viya is used across industries for applications such as fraud detection, healthcare analytics, forecasting, customer intelligence, and AI model operationalization. The platform is designed to improve productivity by simplifying complex AI workflows and enabling collaboration between data scientists, analysts, and business users. Backed by decades of analytics expertise, SAS Viya helps organizations transform raw data into transparent and actionable business decisions at scale.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Azure Marketplace
GitHub
Google Cloud Platform
JMP Statistical Software
Microsoft Azure
Model Context Protocol (MCP)
OpenMetadata
Red Hat OpenShift
SAS Analytics Pro
Integrations
Amazon Web Services (AWS)
Azure Marketplace
GitHub
Google Cloud Platform
JMP Statistical Software
Microsoft Azure
Model Context Protocol (MCP)
OpenMetadata
Red Hat OpenShift
SAS Analytics Pro
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/database/technologies/datawarehouse-bigdata/dataminer.html
Vendor Details
Company Name
SAS
Founded
1976
Country
United States
Website
www.sas.com/en_us/software/viya.html
Product Features
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization
