• LLM‑Style Issue Prediction Using JMP Neural Modeling (2026-US-30MP-2970) Manufacturing-fleet issue resolution often relies on manual interpretation of unstructured engineering logs, where outcomes are influenced by inconsistent descriptions or subjective categorization. This study demonstrates how neural predictive modeling in JMP 19 can be applied as an LLM‑style inference framework to improve issue prediction consistency.Rather than generating free‑text responses, thi...
    Skill level: intermediate
    photo of Paulo Herrera Paulo Herrera Applied Materials
  • On the Road Again: Using JMP Workflow to Identify U.S. Commuting Zones (2026-US-30MP-2876) Commuting zones were introduced in the 1990s as a geographic unit to help explain economic ties. They are not tied to population size (like metropolitan areas), so they can be defined for the entire country. Since their inception, the methodology used in their construction has remained unchanged.In this talk, I share my attempts to explore an alternative approach that uses more recent network clust...
    Skill level: intermediate
    photo of Caleb King Caleb King JMP
  • Unlocking SharePoint Connectivity in JMP Using Data Connectors (2026-US-30MP-2934) In this talk, I explain the process of downloading, installing, configuring, and using the SharePoint and OneDrive Data Connectors add-in in JMP. I demonstrate the add-in's effectiveness at connecting to SharePoint and unlocking the power of Query Builder for data sources stored on SharePoint. I also provide useful information for users who may have issues with configuring their connections. &...
    Skill level: intermediate
    photo of Will Morgan Will Morgan JMP
  • Tips, Tricks + Techniques for Data Tables (2026-EU-30MP-2734) JMP has always helped to reduce time to insight – but most users only scratch the surface of what is possible, in many cases overlooking one of the most powerful aspects of JMP: the data table. This session's tips, some that are new for JMP 19 and some that have been in JMP for years, show how creative use of basic table formulas, attributes, and variables can supercharge data preparation, vis...
    photo of Chris Kirchberg Chris Kirchberg
  • Robust Statistical Approaches for Evaluating Dairy Cow Performance & Health in Field Study Using JMP (2026-EU-PO-2786) Accurately assessing milk yield and health outcomes in dairy herds is essential to develop effective nutritional and management strategies, yet variability remains a major challenge. JMP 19 enables thorough analysis of farm intervention data with advanced statistical comparisons, providing robust interpretation of continuous and categorical variables in an intuitive way. Continuous variables (e.g....
    Skill level: beginner
    photo of Antonella Della Badia Antonella Della Badia and others
  • JMP from the Ground Up: Time-Tested Features and the Mindset That Powers Them In this plenary, we invite you on a journey back to the foundational elements that have powered JMP for decades. We explore the core tools and philosophy that have made JMP an indispensable companion for engineers and scientists, from its earliest iterations to its present-day innovations. Hear from John Sall and others about how these fundamental features came about and continue to evolve. Whether...
    Plenary
    photo of John Sall John Sall and others
  • 開会のご挨拶／基調講演：イノベーションの拡大：エンジニアリング・ワークフローへのデータサイエンス統合 10:00～10:15：開会のご挨拶10:15～11:15：基調講演今日のエンジニアリングにおける課題は、もはや局所的な解決策だけでは不十分です。データサイエンスの手法をデータ分析のワークフローに組み込むための、拡張性が高く柔軟なツールが求められています。JMPの製品群は、統計解析、プロセス最適化、データ視覚化のための強力なプラットフォームを提供し、エンジニアが日々の問題解決を超えて活躍できる環境を創造します。このセッションでは、複雑で大規模な問題への取り組みに焦点を当て、JMPがどのようにエンジニアリング・データサイエンスを支援するかを深掘りします。あわせて、データアクセス、プロセススクリーニング、環境モニタリング、グループ別分析、モデル・応答スクリーニング、そしてJMP Liveとの統合といったツールに焦点を当て、JMPが多様なニーズにどのように対応するかを解説します。具体的な事例やデモ...
    Skill level: beginner
    photo of Jules Parris Jules Parris and others
  • Using JMP to Improve and Automate Analytic Workflows in Complex Processes (2025-US-30MP-2498) Are your organization’s data practices inefficient and delivering inflexible reports? The ingredient company Amyris has built out the capabilities to generate an unprecedented scale of data in the synthetic biology industry by integrating automation, data capture, and analytics. A review of current data operations established that JMP is a powerful tool for scientific analysis methodologies a...
    Skill level: beginner
    photo of Stefan Moser Stefan Moser
  • Evaluating the Impact of Torpedo Bats in Major League Baseball Using JMP (2025-US-PO-2409) Torpedo bats, which diverge from the traditional tapering bat shape, have drawn widespread attention following a surge in power production from players adopting them. While the spike in home runs has sparked public interest, this project investigates whether the unique bat design corresponds with measurable changes in player performance. Using MLB Statcast data accessed via PyBaseball and Baseball ...
    photo of Ryan Cooper Ryan Cooper and others
  • Navigating the New Data Grid, Column Tags, and Filtered Views in JMP 19 (2025-US-30MP-2319) Change is inevitable, but in JMP 19, change is designed to enhance your efficiency and workflow. Much like Scurry and Sniff in Who Moved My Cheese?, those who embrace these enhancements will find themselves working smarter and adapting effortlessly. Three features in JMP 19 deserve to have the spotlight: The new Data Grid provides a more intuitive and flexible interface.  Col...
    Skill level: beginner
    photo of Mandy Chambers Mandy Chambers
  • Two Data Tables and a Microphone: Unlocking the Power of the Tables Menu (2025-US-30MP-2509) Beneath the many layers of JMP's functionality lies a deceptively small but immensely powerful feature set: the Tables menu. While often overshadowed by flashier platforms and analytics tools, the Tables menu is the quiet powerhouse that turns messy, inconsistent data into structured gold. In fact, I would argue that true JMP mastery begins – not ends – with deep fluency in the Tables me...
    Skill level: beginner
    photo of Nathan Clark Nathan Clark
  • What a Mess! Cleaning Up Imported PDF Data with Column Formulas (2025-US-30MP-2543) Most of our data in R&D comes from databases, Excel, or CSV files, or is entered directly into JMP. But supporting data often comes in other formats, most notably PDF files. For example, think of chemical reference tables, vendor information sheets, or even historic company data that now only exists in PDFs, . This type of supporting information can be very helpful to complement experiment...
    photo of Monique Roerdink Lander Monique Roerdink Lander JMP
  • Helper Functions for Exploratory Data Analysis (2025-EU-PO-2104) Data visualization with JMP is like navigating through a maze – both involve finding clarity through complexity. But with JMP, you’re not just solving a puzzle, you’re unlocking a whole new level of insights with data visualization and interactive features. Isn’t it cool how data can guide us through even the most tangled paths?In this talk, I present helper functions that make working with JMP eve...
    photo of Holger Specht Holger Specht OSRAM International GmbH
  • JMP Integration with AWS (2025-EU-PO-2245) We are pleased to present how JMP plays a major part in our data environment at Soitec. With more than 600 users at our company, it is always a challenge to enhance the user experience and industrialize our products deployed on JMP.  Today, JMP allows many data sources to be targeted but collecting data from AWS services can still be overly complex.  Starting with JMP 15 and tha...
    Skill level: advanced
    photo of Guillaume Bugnon Guillaume Bugnon and others
  • Scaling Innovation: Integrating Data Science into Engineering Workflows Today’s engineering challenges demand more than localized solutions – they require scalable, flexible tools that integrate data science techniques into the fabric of data and analytic workflows. The JMP family of products enables engineers to move beyond routine problem solving by providing powerful platforms for statistical analysis, process optimization, and data visualization. This plenary sessi...
    Plenary
    photo of John Sall John Sall and others
  • JMP Add-In Builder for Automating Microbial Growth Characterization (2024-US-30MP-1719) Microbial growth assays using microtiter plate readers are commonly used in the biopharmaceutical industry for screening media components. These assays can generate large amounts of data very quickly; thus, automated approaches to the de-bottleneck the data analysis step are critical to enable faster decision making. At Kerry, retrieving, cleaning, and formatting the growth assay data is a manual p...
    photo of Kyle Probst Kyle Probst and others
  • Make JMP Better by Reporting Your Crashes and Telemetry (2024-US-PO-1878) If you’ve ever had the misfortune to encounter a JMP crash, you have probably encountered a prompt asking you to send JMP your crash files. (Side note: please send us your crashes and provide your email if you’d like to work with JMP Technical Support.) If you send your files, they are combined with those from internal testers and customers all over the world and are fed into the JMP Crash Sys...
    Skill level: beginner
    photo of Shannon Conners Shannon Conners JMP
  • Predicting the Next NFL Passing Yards Leader: A Data Visualization Journey (2024-US-PO-1770) Tom Brady is generally considered the best quarterback in NFL history. His record for most career passing yards is one of the many impressive records he has. To achieve this, he consistently maintained a high passing yards total per year, had the most passes attempted and completed, avoided season-impacting injuries, and had a long career overall. Records are made to be broken. The next q...
    Skill level: beginner
    photo of Yasmine Hajar Yasmine Hajar and others
  • Developing a Unit Conversion Add-In Using JMP 18 Python Integration (2024-US-PO-1892) The units of physical quantities are extremely important to scientists and engineers. They communicate a lot but, unfortunately, can lead to huge and costly mistakes. An add-in has been developed to help manage units within JMP and reduce these errors. This add-in uses the new JMP 18 Python integration to easily do what would have been difficult to achieve in JMP 17. This presentation shows the cap...
    Skill level: advanced
    photo of Evan McCorkle Evan McCorkle JMP
  • Streamlining Manufacturing Excursion Investigations with JMP (2024-US-30MP-1723) Excursions can lead to significant costs at a manufacturing facility. In the semiconductor industry, production downtime, scrapped and low-yield wafers, and decreased output can result in substantial revenue losses. Engineers tasked with investigating these excursions must quickly uncover actionable insights for data-driven decisions that minimize downtime and improve product quality...
    photo of Ryan Cooper Ryan Cooper JMP
  • Remote, Hybrid, In-Office, Anywhere: Trends in Workplace Flexibility (2024-US-30MP-1900) The debate over returning to the office vs working remotely (whether that be home or anywhere else) has caused lively discussions over the past several years. Many companies have called for the full return of employees to the office while others have maintained hybrid or fully remote options. Both authors have transitioned from full-time in-office jobs to full or partial remote work and h...
    Skill level: beginner
    photo of Wendy Tseng Wendy Tseng and others
  • Building Your JMP Ecosystem
    Platform Presets to Powerful Custom Applications     This plenary session explores the many ways of using JMP, JMP Pro, and JMP Live to build customized solutions for your organization’s exact needs, all the way from simple out-of-the-box customizations using tools like Data Connectors, Workflow Builder, and Platform Presets, to building sophisticated custom applications using the JMP Scripting Language. We showcase a variety of real-world examples, ...
    Plenary
    photo of John Sall John Sall and others
  • Speed Squared with JMP JMP is fast. Its interface is designed for ease and efficiency, and its algorithms under the hood are lightning quick. In fact, many users adopt JMP because it empowers them to make data discoveries with exceptional speed. But much like a souped-up car goes fastest when paired with a skilled driver, JMP operates at its fastest when paired with a user who knows how to “drive” it efficiently. Join Ro...
    photo of Olivia Lippincott Olivia Lippincott
  • Tonisity: Our Journey from Excel to JMP Automations (2024-EU-PO-1635) We started using JMP four years ago. We were tired of Excel’s bulkiness, and we loved JMP’s drag-and-drop features and how easy it is to learn. However, we have come a long way since then, currently using JMP for statistics and, more importantly, for automations and product QC. This meta-analysis is just one example of the time and effort we have saved by using JM...
    photo of Stefan Gabriel Buzoianu Stefan Gabriel Buzoianu Tonisity International
  • Use of JMP for Restructuring and Analysis of DOE Data for Pigment Stability Optimisation (2024-EU-PO-1602) A small DOE was prepared by our formulation development project team. The project required the examination of a large number of different, measured responses to investigate the optimisation of pigment stability in a new, experimental paint formulation. However, the team had difficulty obtaining clear guidance from their analysis of the results. Through the use of JMP’s data restructuring tools, i...
    photo of John Steele John Steele AkzoNobel
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