Hello, I've just implemented my first Data flow that basically takes several tables from a SQL Server DB and makes some basic cleaning and transformation. I then chose as the destination a newly created Lakehouse within Fabric since I want to process it further through a notebook. My problem is that no matter how many times I do it, I don't see the result of the data flow as a table in the lakehouse, instead I see it as a schema and a folder structure with the name "Without identification" (the table name I chose in the data flow was "silver_data"). When I click on the "Sin identificar" folder I see a toaster message saying "These objects can not be identified as tables. To maintain them in lakehouse, move them to Files". This makes the access to the "table" quite impossible with pyspark. Is this the expected behaviour? Or am I missing something? (I'm new here😅) Thank you very much in advance!

Hello everyone! I'm new here and I was wondering if anyone could shed some light on the comparison of Fabric and Databricks. I recently started working in a company that wants to integrate a new data analytics platform from scratch (so far they've resolved their analytics needs with the traditional excel and some more advanced users have created easy Power BI dashboards). We are working with a partner for this integration and they've advised us to use Databricks, but I wonder whether Fabric would be a better unified solution and more suitable in the long term. Thank you very much in advance!😊