Is there any way to encrypt the warehouse table column in Fabric?

Hi All, anyone dabbled with dataverse to fabric integration? Any gotchas that I would need to be wary of ?

I am working with an API that does pagination via bookmarks. In the response JSON file there are 2 string value pairs that are used for identifying more records and the parameter to pass in the next request URL. The JSON is structured like this. { "Items": [ { ... }, { ... } ], "Bookmark": "<B><P><p>job</p><p>suffix</p><p>site_ref</p></P><D><f>false</f><f>false</f><f>false</f></D><F><v> 1</v><v>0</v><v>BLGS</v></F><L><v> 783</v><v>0</v><v>BLGS</v></L></B>", "MoreRowsExist": true, "Success": true, "Message": null } When setting up the Pagination rules in the Copy Data activity, how can I pass the value in the Bookmark back to the Relative URL? My current Relative URL looks like this, @concat('IDORequestService/ido/load/',item().source_table,'?filter=',item().FILTER,'&loadtype=NEXT&Properties=',item().cols,'&recordcap=',pipeline().parameters.recordcount,'&bookmark=') I need to add the bookmark parameter at the very end. In Azure Data Factory it is done via a parameter set in the Linked Service but since that doesn't exist in Fabric I'm stuck at getting this to work. I can handle the pagination in a notebook easily, but I wanted to explore using a Data Pipeline to try a more Metadata driven approach.

Hello i am new Power BI and have to migrate Power BI to MS Fabric. What user permissions needed for the migration is workspace admin enough or we need even tenant admin as well. once the tenant of the MS fabric created just reassigning the workspace from Power BI MS fabric will do ? or do we have any step by step documents which can help me to achieve this. Also i do have some of the workspace where i am the ownder and for am not the owner. How do i identify who is owner when i do see the contact details for that workspace. what all are the pre checks i need to take care

Quick question for the group: How are your data engineers positioned within the business? In our proposed model, IT is responsible for extracting and landing source data into Bronze (raw/delta) in a Fabric Lakehouse, while data engineers sit closer to the business and own Silver and Gold transformations, including semantic/analytical modelling. Keen to hear how others have structured this in practice and what’s worked (or not).