Summary
There are different ways of viewing the People list, thanks to pre-defined list views. All views are coming from the same data, but they may have filters, grouping, or less columns to show. This is a short guide to the different views available in the People list.
Details
To switch views in the People list, simply use the navigation tabs on the right. If you apply specific filters, you can bookmark those changes by clicking the "Save View As" option in the drop-down. This would create a personal view (visible only to you) that is a copy of the standard view you were in, but with your own filters applied.
Start Here
This view contains only the most frequently used fields, such as name, job title, department, school, email and a picture. Use this view when you need to quickly access a specific contact. This view is the default view when clicking either the People menu or People -> All Contacts sub-menu.
All Items
All available columns with no filters applied. Use this view when exporting to Excel or CSV.
Easy Filters
A more narrow version of All Items, focused on the fields that are more frequently used for filtering. The filters for most columns have already been pinned to the filters panel. This view is used by all the "By Contact Type" options under the People menu. Use this view to quickly filter by the most common fields.
Members
Displays a list of center members only. This view includes EFDC Leadership, whose members are also considered EFDC members.
Newest Members
A minimal view used primarily to highlight new members on the TrackMaster home page. Do not use.
Speakers
A custom view formatted as a timeline and filtered only for those people who have had speaker engagements. This view is used primarily in the Speaker History page. Do not use.
System Views (zSystem-*)
System views required for automation. Do not use.
Notes
Resources
About the Author
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Gabriel Mongefranco is a Mobile Data Architect at the University of Michigan's Eisenberg Family Depression Center. Gabriel has over a decade of experience with automation, data analytics, database architecture, dashboard design, software development, and technical writing. He supports U-M researchers with data cleaning, data pipelines, automation and enterprise architecture for wearables and other mobile technologies.
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