I am working in Microsoft Fabric and need to use two Lakehouses in the same notebook (later inner join between 2 tables from 2 lakehouse or join using 2 dataframes). I can read data from the default Lakehouse (for example: df_mean = spark.sql(sql_trainer)), but I cannot read tables from a second Lakehouse that is not set as default. What is the correct way to read tables from the second Lakehouse?

I have silver layer fabric workspace which has numerous notebooks under folder called "common". e.g one of the notebook is called Env_Config which basically identifies environment and then depending on environment, it does some basic variables configuration. Another notebook is called "shared functions" , a central notebook with all UDF. Now I am at the stage where I am working on gold layer where I need similar code to identify the environment and other basic configuration and shared functions. I am creating similar notebooks in gold because my understanding is, it is sounding like duplication but it is controlled duplication and seems fabric pattern. Am I right with above approach or are their any other alternatives or suggestions to avoid it?

Which is the best approach for this integration?

The SharePoint site contains folder like structure say year/month/date in that (list of files) and files are incrementally added every day so how to load the data in same format in Fabric Option 1: By creating a connection( with tenant details) using copy data can able to load only the schema of the files in the lakehouse not the physical tables Option 2: Using the dataflow gen2 failed to run the query as the data for the one month is more then 5GB Please suggest an optimise way to connect SharePoint of fabric

What is the best practice to migrate(dataflows, lakehouses, notebooks) from one workspace to other workspace