Jmp 17 Pro May 2026
Marketing analysts use JMP 17 Pro’s Time Series platform to forecast Q4 sales. The new "Dynamic Linear Models" (DLMs) handle missing data gracefully—a common issue with retail panel data. Pro users can then take the forecast into Model Screening to identify which marketing channels (TV, digital, print) have the highest causal impact, visualized via a Shapley Additive Explanations (SHAP) plot.
JMP Pro differentiates itself from the standard version through its robust suite of machine learning tools. JMP 17 introduces specific upgrades that address modern data science requirements.
3.1 Neural Network Architecture The Neural Network platform has seen significant overhaul. JMP 17 Pro allows for more complex architectures with deeper layers. The introduction of new activation functions (such as Exponential Linear Unit) and the ability to easily export the final model formula make it a viable competitor to Python-based libraries like TensorFlow or Keras for standard tabular data problems, all within a no-code environment.
3.2 Model Screening and Comparison A critical step in the data science lifecycle is model selection. JMP 17 Pro refines the Model Screening platform, allowing users to run multiple model types (Neural, Boosted Tree, Random Forest, etc.) simultaneously and compare them via cross-validation. The improvements in JMP 17 provide clearer diagnostics regarding model overfitting and prediction variance, streamlining the path from raw data to deployed model.
3.3 The Prediction Profiler The interactive Profiler remains JMP’s flagship feature for understanding model behavior. In JMP 17, the Profiler has been optimized for speed. For high-dimensional models, the responsiveness of the profiler sliders has improved significantly, allowing for real-time "what-if" scenario planning without the computational lag associated with previous versions.
To run JMP 17 Pro effectively (especially for large data or neural networks), SAS recommends:
Note: JMP 17 Pro is not supported on 32-bit systems or Windows 7.
JMP Pro 17
A yield engineer imports a 5-million-row dataset of wafer test probes. Using Graph Builder in JMP 17 Pro, they color-code failing bits by spatial location on the wafer. They then use the Model Screening tool to automatically try 20 different machine learning models to predict fail rates based on 50 input sensors, finding that a Boosted Tree model isolates a specific etching step as the root cause.
JMP 17 Pro comes with the latest iteration of JMP Scripting Language (JSL) . New scripting additions include:
For organizations, this means nightly reports can be generated automatically, emailed to stakeholders as interactive HTML, and logged without manual intervention.
JMP 17 Pro is a strong upgrade for organizations needing interactive statistical discovery, reproducible analyses, and a comprehensive set of classical and advanced statistical tools. It’s particularly well suited where visual, iterative exploration and DOE workflows are central; evaluate integration needs and licensing against your organization’s ML/engineering stack.
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JMP 17 Pro, released in October 2022, introduced several features designed to automate workflows, simplify experimental design, and handle complex data sets . As a subsidiary of JMP Pro 17
provides advanced predictive modeling and cross-validation techniques beyond the standard version Core New Features in JMP 17 Pro Workflow Builder
: A point-and-click interface that records analysis steps, allowing you to create documented and reproducible workflows without writing scripts. Easy DOE (Design of Experiments)
: A guided, step-by-step platform that simplifies the process of designing and analyzing experiments for users of all skill levels. JMP Search
: A global search tool that helps you quickly find and launch specific analysis platforms or help documentation. Sample Size Explorers
: Interactive platforms that help determine the necessary sample size for various statistical tests before starting a study. Functional Data Explorer Enhancements
: JMP Pro 17 includes specialized tools for modeling spectral data (e.g., IR, Mass Spec) and other data that is inherently functional. Specialized Analysis for Professionals JMP Live 17: Kicking Collaboration Up a Few Notches
JMP Live 17: Kicking Collaboration Up a Few Notches | JMP. ON-DEMAND WEBINAR. JMP Live 17: Kicking Collaboration Up a Few Notches.
Exploring the Power of JMP 17 Pro: A Modern Standard for Advanced Statistical Analysis
In the rapidly evolving world of data science, having the right tools to navigate complex datasets is essential. JMP 17 Pro, developed by the JMP subsidiary of SAS Institute, has emerged as a cornerstone for scientists, engineers, and researchers seeking a bridge between simple spreadsheets and heavy-duty coding environments. This version introduces more enhancements and new platforms than any previous release, solidifying its place as a top-tier choice for predictive modeling and exploratory data analysis. What Sets JMP 17 Pro Apart?
While the standard JMP software is excellent for visual exploration and basic statistics, the Pro version is specifically designed for the needs of data scientists. It extends the base capabilities with advanced predictive modeling, cross-validation techniques, and tools specifically tailored for "wide data"—datasets with thousands of variables often found in genomics and manufacturing. Key Capabilities of JMP 17 Pro:
Predictive Analytics: Features like Model Screening allow users to build and compare multiple candidate models (such as neural networks and decision trees) simultaneously to find the best fit.
Genomics and Wide Data: A major breakthrough in version 17 is the ability to perform high-speed genomic data analysis directly within the software, moving away from previous dependencies on a SAS backend.
Advanced Automation: Tools like the Workflow Builder enable users to record and automate repetitive data preparation and analysis tasks without writing a single line of code. New Features in the JMP 17 Release
The release of JMP 17 Pro brought several transformative tools that simplify complex workflows:
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JMP 17 Pro, released in October 2022, is the advanced version of the JMP statistical discovery software. It builds upon the core features of JMP 17—such as the Workflow Builder for reproducible analysis and Easy DOE for guided experiment design—by adding sophisticated predictive modeling and specialized analytical tools0;bb7;0;809;. 0;16;
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JMP 17 Pro introduced several high-impact platforms and improvements: 0;16; 0;4f8;0;412;
Workflow Builder: A point-and-click tool that lets you record, document, and share reproducible analysis sequences.
Genomics and Wide Data0;407;: Optimized performance for tables with thousands of variables, including new platforms like Marker Statistics, Marker Simulation, and Multivariate Embedding.
Advanced Modeling0;449;: Includes Generalized Regression enhancements like SVEM (Self-Validated Ensemble Models) for small data or mixture experiments.
Text Explorer Upgrades: While standard JMP handles basic word clouds and term frequency, JMP Pro 17 offers advanced text mining like Latent Semantic Analysis (LSA)0;b06;, Topic Analysis, and Sentiment Analysis.
Functional Data Analysis: Tools for analyzing spectral data or other data that occurs as a continuous function or curve. 0;2a;
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JMP Pro is designed for more complex data challenges. Key differences include: 0;16;
Predictive Analytics: Automated decision-tree building in the Partition platform and cross-validated stepwise regression.
Advanced Regression0;c1d;: Partial Least Squares (PLS) and structural equation modeling (SEM) are specialized for the Pro version.
Simulation & Fitting: More robust tools for simulating data and fitting models to complex datasets. 18;write_to_target_document7;default0;822;18;write_to_target_document1a;_0ALuaaL6OcOiptQP2YqbgQ8_20;2a; Practical Resources 0;16;
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JMP 17 Pro introduced significant enhancements focused on automation, ease of use, and advanced modeling for scientists and data scientists. JMP Statistical Discovery Key New Platforms and Tools Workflow Builder
: A standout feature that acts as a point-and-click macro recorder. It allows you to capture your analysis steps and replay them as a documented, reproducible workflow that can be shared as a package.
: A guided platform designed to lead new users step-by-step through the design and analysis of an experiment, offering both guided and flexible modes. JMP Search
: An interactive tool to quickly find and launch specific analyses, menu items, or sample data within the software. Sample Size Explorers
: New platforms specifically built for interactive power and sample size calculations. JMP User Community Advanced Modeling and Machine Learning (Pro Features) Functional Data Analysis (FDA)
: Enhanced tools for analyzing spectral data, sensor streams, and time series by converting discrete measurements into continuous functions. Autotune for Hyperparameters
: A new option that simplifies the tuning of machine learning models using a "Fast Flexible Filling" design. XGBoost Add-in
: Integration for one of the most popular gradient boosting algorithms directly within JMP Pro. Wide Data Optimization
: Improved performance and new platforms (like Marker Statistics and Marker Simulation) specifically for genomics and other "wide data" problems with thousands of variables. JMP User Community Core Data & Visualization Improvements Operations Preview
: You can now see a preview of data table operations—like joining, stacking, or splitting—before clicking "OK". Graph Builder Updates
: Support for plotting multiple responses and displaying tabular data (like reference lines and statistics) directly within graphs. Data Preparation
: New tools for standardizing column attributes, tokenizing text data with Text Explorer , and using advanced formulas to compute new variables. JMP User Community Official Learning Resources Marketing analysts use JMP 17 Pro ’s Time
JMP 17 Pro is a sophisticated statistical discovery software from JMP Statistical Discovery LLC, a subsidiary of SAS Institute. Designed specifically for data scientists, engineers, and researchers, the "Pro" version extends the capabilities of standard JMP with advanced predictive modelling, machine learning, and cross-validation tools. Core Capabilities and Use Cases
JMP 17 Pro is used across diverse industries, including biopharmaceuticals, semiconductor manufacturing, and environmental sciences.
Predictive Modelling: It provides a suite of machine learning algorithms, including neural networks, random forests, and gradient-boosted trees, allowing users to build and validate complex models without writing code.
Design of Experiments (DOE): Features like the new Easy DOE guide users through designing and analyzing experiments step-by-step.
Functional Data Analysis: Advanced spectral data analysis and functional data explorer tools enable the modelling of data over time or space.
Mixed Models: It supports modelling random effects and non-normal distributions (e.g., Poisson, Binomial) through the Generalized Linear Mixed Models (GLMM) personality. Key New Features in Version 17
The release of JMP 17 Pro introduced several significant productivity and analytical enhancements:
Workflow Builder: A point-and-click tool that records interactive sessions into graphical scripts for repeatable data preparation and reproducible analysis.
JMP Search: An interactive feature that helps users find specific menu items, tutorials, or analysis tools directly within the interface.
Enhanced Data Cleaning: Tools like the upgraded Columns Manager allow for rapid identification of missing data and batch modification of column attributes.
Table Previews: Users can now preview operations like join, concatenate, or stack before committing changes to the data table. JMP Pro vs. Standard JMP
While both versions share core graphical discovery features, JMP Pro offers exclusive tools for more rigorous scientific inquiry: New Features in JMP 17
JMP 17 Pro is the high-performance version of JMP's statistical discovery software, designed to handle large-scale predictive modeling and complex data challenges. Released in October 2022, this version introduced more new platforms and enhancements than any previous release, focusing on workflow automation and advanced modeling for scientists and engineers. 🚀 Top New Features
Workflow Builder: A point-and-click tool that records analysis steps into a shareable, reproducible script.
Easy DOE: A step-by-step guided platform for designing and analyzing experiments, making complex Design of Experiments accessible.
JMP Search: A global search tool to quickly find and launch specific analysis platforms or help tutorials.
Sample Size Explorers: Interactive tools to determine the necessary sample size for various statistical tests. 🧬 Advanced Pro Capabilities
JMP 17 Pro is a powerhouse for advanced statistical analysis and predictive modeling. This version is packed with massive improvements specifically geared toward data scientists, engineers, and researchers handling complex, multi-variable data.
Here are the standout features that make upgrading or utilizing this specific build highly valuable: 🚀 Top Advanced Features in JMP 17 Pro
Workflow Builder (Macro Recorder): You can record your manual point-and-click analysis steps and instantly replay or package them to automate repetitive workflows.
Functional Data Explorer (FDE) Enhancements: Preprocessing spectral and raw sensor data is drastically easier with native tools like Standard Normal Variate (SNV) and Savitzky-Golay derivatives built right into the platform.
Automated XGBoost Hyperparameter Tuning: The standalone XGBoost add-in now includes an Autotune option using Fast Flexible Filling designs, saving hours of manual trial and error.
SVEM for Complex Mixtures: Self-Validated Ensemble Models (SVEM) allow for highly precise predictive modeling when evaluating complex mixture-process experiments.
Genomics and Wide-Data Scaling: Core data table operations have been heavily optimized to compute massive, thousands-of-variables datasets exponentially faster than before. 💡 Pro-Tips for Maximizing Your Output
JMP 17 Pro is widely considered a significant update, introducing several features that streamline reproducible analysis and advanced modeling. Key Improvements in JMP 17 Pro
Workflow Builder: A standout feature that allows users to record their interactive analysis steps and save them as a script. This makes complex data cleaning and analysis highly reproducible without requiring extensive coding.
Easy DOE: A guided Design of Experiments (DOE) platform that helps users through the entire process of designing and analyzing experiments step-by-step.
Functional Data Explorer (FDE) Enhancements: Specifically for Pro users, this platform now includes built-in preprocessing for spectral data, such as baseline correction and smoothing, which is essential for chemists and material scientists. JMP Pro differentiates itself from the standard version
JMP Search: A new search tool that lets users quickly find specific platforms, analysis options, or menu items by typing keywords.
Genomics and Wide Data Performance: Version 17 Pro is optimized for handling the large, wide datasets common in genomics, reportedly performing analyses in minutes that previously took hours by keeping data in-memory. User Perspectives Spectral analysis in JMP 17 and JMP Pro 17
JMP 17 Pro is a high-performance statistical discovery software designed for scientists, engineers, and data analysts who require advanced predictive modeling and machine learning capabilities. Released by SAS, it builds upon the standard JMP 17 platform by adding tools for handling complex data sets and cross-validation, making it a preferred choice for research in fields like biopharmaceuticals and semiconductor manufacturing. Key New Features in JMP 17 Pro
The 17 Pro release introduced several major enhancements aimed at automating workflows and deepening analytical power:
Workflow Builder: A standout addition that acts as a macro recorder. It allows users to capture a series of data cleaning and analysis steps and replay them on new data, significantly increasing reproducibility.
Generalized Linear Mixed Models (GLMM): JMP 17 Pro expanded its "Fit Model" capabilities to include GLMM, allowing users to model non-normal distributions (like Poisson or Binomial) while simultaneously accounting for random effects.
Functional Data Explorer (FDE) Updates: Specifically for Pro users, the FDE now supports Wavelets for spectral data analysis, which is crucial for high-frequency or signal-based data.
Enhanced Tables Menu: A new "Operations Preview" allows users to see the result of a join, stack, or concatenation before committing to the change. Advanced Analytics and Machine Learning
JMP 17 Pro is distinguished from the standard version by its focus on predictive accuracy:
Predictive Modeling: It includes advanced algorithms such as Neural Networks and Regression Trees with built-in cross-validation to prevent overfitting.
Design Space Profiler: This tool helps engineers optimize processes by visualizing how various factors interact within a defined design space.
Model Screening: Recent improvements allow for faster comparison across dozens of different models to identify the most effective predictor for a given outcome. System Requirements and Availability JMP 17 Pro is compatible with both Windows and macOS:
Unlocking High-Performance Analytics with JMP 17 Pro For data scientists and researchers, the "workflow" isn't just a series of steps—it's the core of discovery. JMP 17 Pro
was designed specifically to minimize obstacles in that process, allowing users to focus more on what the data is saying and less on the mechanics of the software. Key Breakthroughs in JMP 17 Pro
JMP 17 Pro introduced several advanced analytical capabilities that set it apart from previous versions and the standard JMP edition. Generalized Linear Mixed Models (GLMM): A major addition for advanced users, the GLMM personality in Fit Model
allows for modeling non-normal distributions (like counts or proportions) while simultaneously accounting for random effects such as blocking. Workflow Builder:
This tool acts as an interactive macro recorder, capturing your analysis steps in a graphical script. It is perfect for automating repeatable data preparation or creating reproducible analysis packages to share with colleagues. Functional Data Explorer (FDE) Enhancements:
For those in chemistry or materials science, JMP 17 Pro added powerful wavelets and spectral analysis tools to preprocess and model high-dimensional spectral data. Design Space Profiler:
This platform helps optimize processes within a defined design space, making it a critical tool for engineers and manufacturing specialists. Why Professionals Choose JMP Pro
While the standard JMP software provides excellent visual exploration,
is built for those handling large, messy, or incomplete datasets. Predictive Modeling: It offers a rich set of algorithms for machine learning and neural networks
, allowing you to screen and compare multiple models efficiently. Enhanced Integration: JMP 17 maintained a flexible relationship with external environments like Python
, utilizing the user's environment for specialized coding needs. Clinical and Genetic Analysis:
Specialized tools for direct import of genomic data and advanced clinical trial monitoring (available through JMP Clinical) leverage the Pro engine for high-speed performance. Python Code unable to generate output in JSL (JMP 17 Pro) 5 Apr 2025 —
Since there is no widely recognized commercial product specifically named "JMP 17 Pro" (JMP software is simply branded as JMP—with version numbers like 17—and the "Pro" designation typically belongs to Adobe Acrobat), I have created this guide assuming you are referring to the latest release of JMP Version 17.
If you are a new user or upgrading, this guide covers the interface changes, key new features, and how to perform essential data analysis tasks in JMP 17.
If you want to visualize data quickly, use Graph Builder.