Do you know why archiving five fact sheets in one bulk Excel upload can't simply be undone by re-uploading the same rows with the archive status removed? This session is a fully hands-on troubleshooting exercise inside a live SAP LeanIX instance: bulk-exporting fact sheets to Excel, filtering data down to specific IT components, re-importing changes, and working through real upload errors as they happen. If you've ever wondered what actually goes wrong during a bulk data operation in LeanIX, and how to fix it live, this session shows the real, unfiltered process.
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Chapters:
0:00 - Fixing the fact sheet view setting
3:56 - Demo transition: hands-on with a live tenant
6:38 - Marking rows for bulk archiving in Excel
16:19 - Finding archived items via Previous Imports / Trash
22:45 - Enabling Full View for another participant
33:44 - Explaining Action column & internal ID vs display row logic
51:02 - What 'Broken Quality Seal' means
1:13:24 - Encouragement: practice more scenarios at home
1:32:49 - Recap of the meta model structure (layers)
1:37:34 - Live troubleshooting: mismatched tech category/tech stack naming
In this video, you'll learn:
How to troubleshoot a common visibility issue where users only see a subset of fact sheet types, and how filter/provider settings cause it
How to use Inventory Tools to export fact sheet data to Excel for bulk editing and mock-up purposes
How the active fact sheet count changes as records get archived, and how to track that shift through export counts
How to bulk-archive multiple fact sheets at once using a properly formatted Excel import, using IT components as the working example
Why archived fact sheets can't simply be "recovered" by re-uploading the same rows with the archive status removed, and what LeanIX's real limitation is here
How to filter fact sheet data by provider and other attributes before exporting, to isolate exactly the records you need to work with
Live, real-time debugging of an actual import error (a batch update failure on ~1,600 rows), including how to read and interpret the error output
Watching a real import error happen and get debugged live is far more valuable than any clean, error-free tutorial, this is genuinely what working with bulk data operations in LeanIX looks like on a real project.
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