Select customers were invited to our London office for a workshop on data preparation in JMP with Learning Strategy Manager, Julian Parris (@julian). You can find a description below.
https://www.youtube.com/watch?v=JucYsEBfEx8
Materials used in the workshop and resources for further learning are attached. (For exercise 3, in order to make the map visuals work, you need to have the two "district_burrough..." jmp data tables saved in the same folder as the LifeSat table that you are working from). Please let me (@phil_kay) know by comment below if you have any questions or need anything else.
Resouces for further learning suggested by Julian
Webinar topics from the Mastering JMP Series:
Overall list:
https://www.jmp.com/mastering
Automating Analyses Using JMP Scripts
https://www.jmp.com/en_us/events/mastering/topics/automating-analyses-using-jmp-scripts.html
Some of my webinars on specific topics I mentioned:
Multivariate Analysis and Advanced Visualization
https://www.youtube.com/watch?v=bQWCgJCea20
The Scientific Workflow in JMP: Creating Reproducible Analyses:
https://www.youtube.com/watch?v=6NWDcfWrhMA
JMP Integration and Extensibility with SAS, R, Python
https://www.youtube.com/watch?v=QLQQXFzjufQ
Finally, a few of us were talking about health data so I wanted to pass along these links:
Hidden URL where you can request that Garmin send you a package of your health data (required now by GDPR): https://www.garmin.com/en-GB/account/datamanagement/exportdata/
My Copenhagen talk: Narcististic - Lessons learned (about JMP and life) during a 14k+ mile journey collecting, analyzing, and visualizing personal health data:
https://www.youtube.com/watch?v=27KT8bvDCw0
Example of analysis that participants created after getting the data analytics-ready (interactive)
You can find the interactive analytics examples from the workshop in JMP Public.
Workshop Description
Rarely, if ever, do data come to us analysis-ready. Scientists and engineers tell us that more than 80% of their work with data is spent on preparation, leaving little time for exploring and extracting insight. In extreme cases your data might be so messy that you can’t imagine that you will ever be able to use them to answer your important technical questions. These common challenges prevent organisations from realising the full value of data analytics to reduce costs and speed products to market.
Luckily, JMP has a rich set of tools that enable you to efficiently prepare your data for analysis. In this workshop you will explore 10 of the essential tools in JMP to help you get your data from “messy” to “analysis-ready”.
Through a combination of case study demonstrations and hands-on exercises you will learn how to handle:
• table restructuring and joining,
• computed and derived variables,
• outliers and influential points,
• recoding of variables,
• missing values,
• and more….
After we explore each of the 10 essential tools in depth and discuss best practices (and even some “off-label” uses for certain tools), we’ll work through three case studies where we will apply these tools in various ways to efficiently import, recode, restructure and reorganize complex and challenging data sets. Previous experience using JMP is highly recommended, though not strictly necessary.
As a new user of JMP I found the workshop very useful ...I now have lots of info and ideas to take back to my collegues who are also at the start of the JMP learning curve and keen to start analysing their data. Thank you for your help.
That is great. Thanks for letting us know, @Sara_R.
Regards,
Phil
I just wanted to say how much i enjoyed the course - i have loads of information now - and even more important i know where to look for help 
