Migrate Your Legacy Public Folder Data to the Most Suitable Target
What’s the Problem with Public Folders?
Exchange public folders have been used to share and collaborate for over 20 years, but the feature has been de-emphasised for some time now, and public folders have various functional and administrative limitations which make them difficult to manage. There are plenty of modern services which offer better collaboration features, superior functionality, and comprehensive management. Public Folder Shuttle migrates legacy data into the most appropriate target in Office 365, the solution enables organizations to bring their public folder data into a new environment, and back under their control.
What is Public Folder Shuttle?
Public Folder Shuttle is a powerful, intelligent solution for legacy public folder migration and analysis. The tool analyzes characteristics within data hierarchies and repositories in Exchange public folders, and classifies their contents. Once analysis is complete, the solution predicts where the data should be placed, provisions the relevant targets (like Office 365 groups), and migrates the selected information to the chosen destination. Public Folder Shuttle can also find redundant and obsolete data, and is able to remove or archive it as required.
How Does Public Folder Shuttle Work?
- Exchange public folders can span extremely large hierarchies and volumes of data. Public Folder Shuttle uses dynamic grouping; its deep analytics can identify logical splits between subfolders in the public folder hierarchy, based on characteristics such as permission sets and common folder properties.
- Exchange administrators can review the output of the analysis before migration, and extend or narrow the scope to remove redundant/irrelevant data.
- Public Folder Shuttle is powered by Deep Analytics Technology (DAT), which automatically analyzes data held in legacy systems, and takes their characteristics into consideration to determine the most suitable modern target system.
- Criteria like size, age, content type, and ownership are compared so that the best recommendation can be made based on current usage, data type and contents.