JMP
JMP is a powerful statistical discovery software providing interactive data visualization and deep analytical capabilities to help scientists and engineers explore data, uncover patterns, and solve complex research problems.
SAS Viya
SAS Viya is a cloud-native data management and analytics platform that helps you build, deploy, and manage artificial intelligence and machine learning models to solve complex business problems efficiently.
Quick Comparison
| Feature | JMP | SAS Viya |
|---|---|---|
| Website | jmp.com | sas.com |
| Pricing Model | Subscription | Custom |
| Starting Price | $142.5/month | Custom Pricing |
| FREE Trial | ✓ 30 days free trial | ✓ 14 days free trial |
| Free Plan | ✘ No free plan | ✘ No free plan |
| Product Demo | ✓ Request demo here | ✓ Request demo here |
| Deployment | ||
| Integrations | ||
| Target Users | ||
| Target Industries | ||
| Customer Count | 0 | 0 |
| Founded Year | 1989 | 1976 |
| Headquarters | Cary, USA | Cary, USA |
Overview
JMP
JMP helps you explore data visually and interactively, moving beyond static graphs to dynamic discovery. Whether you are an engineer optimizing a manufacturing process or a scientist designing clinical trials, you can use its point-and-click interface to uncover hidden trends without writing complex code. You can easily import data from various sources, perform sophisticated regressions, and build predictive models that drive better decision-making across your organization.
The software focuses on the 'discovery' aspect of data science, allowing you to see your data from every angle through linked windows and real-time filtering. It scales from individual researchers to global R&D teams, providing a robust environment for everything from basic descriptive statistics to advanced design of experiments (DOE). By using JMP, you reduce the time spent on data preparation and move faster toward actionable insights.
SAS Viya
SAS Viya is a cloud-native analytics platform designed to help you manage the entire data lifecycle in one place. You can move from raw data to production-ready AI models using a unified interface that supports both visual drag-and-drop tools and popular programming languages like Python and R. This flexibility allows your data scientists and business analysts to collaborate effectively on the same projects.
The platform handles massive datasets with ease thanks to its distributed, in-memory processing engine. You can deploy it on any cloud provider or on-premises environment to maintain control over your infrastructure. By automating repetitive data preparation and model tuning tasks, you can focus on uncovering insights that drive better business decisions and operational efficiency across your entire organization.
Overview
JMP Features
- Interactive Data Visualization Click on a data point in one graph to see it instantly highlighted across all other open windows and reports.
- Design of Experiments (DOE) Build custom experimental designs that solve real-world problems while minimizing the number of expensive runs you need to perform.
- Predictive Modeling Create and validate predictive models using automated techniques like neural networks, decision trees, and bootstrap forest methods.
- Automated Data Cleaning Identify outliers, fix entry errors, and recode data quickly so you spend more time analyzing and less time scrubbing.
- Quality and Process Control Monitor your manufacturing processes with control charts and capability analysis to ensure your products meet strict specifications.
- JMP Scripting Language (JSL) Automate repetitive tasks and create custom analytical applications to share standardized workflows with your entire team.
SAS Viya Features
- Visual Data Preparation. Clean and transform your data using an intuitive visual interface that automatically generates code in the background.
- Automated Machine Learning. Build high-quality models faster by letting the system automatically handle feature engineering, algorithm selection, and hyperparameter tuning.
- Model Management. Register, track, and monitor all your analytical models in a central repository to ensure they perform reliably over time.
- Open Language Support. Write code in Python, R, or Lua while still taking advantage of the platform's powerful distributed processing capabilities.
- Real-Time Decisioning. Embed your analytical models directly into business processes to trigger automated actions and responses the moment data arrives.
- Natural Language Generation. Receive automated text explanations of your data visualizations so you can understand the 'why' behind your business trends.
Pricing Comparison
JMP Pricing
- Full statistical capabilities
- Interactive data visualization
- Design of Experiments (DOE)
- Technical support access
- Annual software updates
- Windows and Mac compatibility
- Everything in JMP, plus:
- Advanced predictive modeling
- Cross-validation techniques
- Text exploration and analysis
- Reliability block diagrams
- Mixed models and uplift modeling
SAS Viya Pricing
Pros & Cons
JMP
Pros
- Dynamic linking between graphs makes data exploration intuitive
- Industry-leading tools for complex Design of Experiments
- Excellent documentation and active user community support
- Powerful scripting language for automating complex workflows
Cons
- High annual subscription cost for individual users
- Steep learning curve for advanced statistical modules
- Interface can feel cluttered with many open windows
SAS Viya
Pros
- Handles extremely large datasets with high performance
- Unified environment for both coding and visual users
- Strong governance features for regulated industries
- Excellent technical support and extensive documentation
- Seamless integration with major cloud providers
Cons
- Higher price point compared to open-source alternatives
- Significant learning curve for the full feature set
- Initial setup and configuration can be complex