Hi @Albert_Benjamin , Thank you for reaching out to the Microsoft Community Forum.
When loading data from MongoDB Atlas into Power BI, older documents may lack newer fields, causing schema inconsistency. Since MongoDB is schema less and Power BI infers the schema based on sampled documents, missing fields won't appear unless you actively handle them.
If you have access to MongoDB Atlas (even read-only), the best non-invasive approach is to create a view that ensures every document contains all expected fields, setting missing ones as null. Views are BI-friendly and avoid modifying your source data. In Power BI, connect to this view instead of the original collection. Now all documents will have a consistent schema and all fields will load correctly even if their values are sometimes null. If you cannot create a view, you can fix missing fields after loading your collection into Power BI. In Power Query Editor, manually add columns for the missing fields, defaulting them to null where they are missing. This ensures all your Power BI tables have the necessary fields for modelling and reporting, even if older documents didn’t have them initially.
If you have write access to the MongoDB collection and want a permanent solution, you can update all older documents to add the missing fields directly, assigning them a default value like null. Though Make sure to back up your data first. This way, all documents natively have a consistent structure before Power BI loads them, reducing the need for complex transformations later.
Views - Mongo DB
db.collection.updateMany()
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Thank you.
