Live In-Person Event
Analytics for Everyone: Upskilling for the Digital Future
Date: 23 September
Time: 10:00-14:00 BST
Location: Royal Society of Chemistry, Burlington House, Piccadilly, London W1J 0BA
Registration: Free to attend, but registration is required.
Across science and engineering, teams are under mounting pressure to work faster, handle growing volumes of data, and adapt to rapid advances in AI and automation.
As AI and automation reshape these fields, many organizations are searching for ways to equip their scientists and engineers with modern analytical capabilities while keeping them closely connected to their data and discoveries.
This seminar explores how interactive and visual analytics enables scientists and engineers to remain at the center of discovery in the digital future. Rather than replacing scientific and engineering expertise, modern analytics should strengthen it – helping experts explore data more deeply, investigate problems more quickly, and make informed decisions with confidence.
Why attend?
- See how scientists and engineers can use interactive analytics to explore data, investigate problems, and make informed decisions without extensive coding.
- Follow practical analytical workflows from data access and preparation to visualization, modeling, optimization, and reporting.
- Explore how AI-assisted workflows, Bayesian optimization, and JMP Live support faster experimentation, collaboration, and discovery.
Topics
- Analytics in the age of AI: Uncover why human-guided exploration remains essential in scientific and engineering workflows, and how interactive analytics complements AI-driven approaches.
- Practical analytical workflows: See examples of how teams move from data access and preparation through visualization, modeling, optimization, and reporting.
- Interactive exploration and discovery: Discover how interactive tools, workflow automation, profiling, and Bayesian optimization help teams investigate data and guide next experiments more effectively.
Who should attend?
This seminar is designed for scientists, engineers, technical specialists, and R&D teams interested in applying analytics more effectively within science and engineering workflows.
No advanced programming or data science background is required.
Reserve your spot now! Limited seats are available.
Agenda
| Time | Topic | Presenter |
| 10:00 | Registration and Coffee | |
| 10:30 | Welcome and introduction | |
| 10:45 |
Analytics for the Digital Future: Keeping Scientists and Engineers at the Center of Discovery A discussion on the growing role of analytics in science and engineering, including analytics in the AI era, and why human-guided exploration remains essential. |
Phil Kay, Director, Presales Support, JMP Statistical Discovery |
| 11.30 |
Industry Case Studies: From Data to Discovery Follow practical analytical workflows covering data preparation, exploration, modeling, optimization and live reporting. See how workflow automation, AI-assisted analysis, and Bayesian Optimization help guide next steps. |
Owen Jonathan, Senior Associate Systems Engineer, JMP Statistical Discovery |
| 12:15 | Lunch | |
| 13:00 |
Applying Analytics: Interactive Techniques for Everyday Problem Solving See demonstrations of Graph Builder, as well as techniques for data preparation, dynamic linking, profiling, and interactive exploration. |
Stuart Little, Senior Systems Engineer, JMP Statistical Discovery |
| 13:45 | Q&A | |
| 14:00 | Meet the Experts |
Speakers
Phil Kay
JMP Statistical Discovery
Phil Kay is the Director of Presales Support for JMP Statistical Discovery, a subsidiary of SAS. His job is to understand the science and engineering challenges and provide guidance on data analytic solutions for industrial organisations around the world.
Previously, Kay was a key scientist in the development of numerous processes for the manufacture of colorants for digital printing at FujiFilm Imaging Colorants. He has a master’s degree in applied statistics with a dissertation on design of experiments. He also has a master’s and Ph.D. in chemistry.
Kay is a Fellow of the Royal Statistical Society, a Chartered Chemist, and a member of the committee for the Process Chemistry and Technology Group with the Royal Society of Chemistry.
He loves showing people how data analytics enables better science.
Stuart Little
JMP Statistical Discovery
Stuart Little is a Senior Systems Engineer at JMP, where he applies a background in the chemicals industry to helping provide solutions to a broad range of data and statistical problems. He has previously been Lead Research Scientist at Croda, a chemical products manufacturer. Little holds a Ph.D. in chemistry from the University of Sheffield.
Owen Jonathan
JMP Statistical Discovery
Owen Jonathan is a Senior Associate Systems Engineer for JMP Statistical Discovery, which creates interactive and highly visual statistical discovery software for scientists and engineers. His role involves identifying critical business issues of customers in the UK and guiding them as they adopt data-driven solutions for their organizations. Jonathan has a master’s in systems and synthetic biology from Imperial College London. Prior to becoming an SE, he joined JMP as an intern where he identified design of experiments (DOE) applications in the field of biotechnology and delivered DOE workshops with relevant case studies to synthetic biologists.
Ben Barroso-Ingham
JMP Statistical Discovery
Ben Barroso-Ingham is a Systems Engineer at JMP. Previously, he has held roles as a Fermentation/Upstream Scientist at Elanco Animal Health and Allergan Biologics, focusing on developing small-scale microbial fermentation models and the application of design of experiments.
He has a Ph.D. in chemical engineering from the University of Manchester, where he focused on the use of DOE in fermentation optimization and analytical method development.