Uisng Fabric jupyter notebook to load/push data from/to Snowflake
Hello Farbic Community I'm new to using Fabric and am exploring its capabilities. I understand that we can load data from Snowflake into a Fabric Notebook via Data Lakehouse. I'm curious if it's possible to use a Python script in a Fabric notebook to directly load data from Snowflake into the notebook without involving a data lakehouse. In addition to direct data import from Snowflake, I'm also interested in whether data can be pushed back to Snowflake. If direct data import/export to and from Snowflake isn't feasible with a Python script in a Fabric notebook, is it possible to accomplish this using Dataflow or Data Pipeline? I would appreciate any suggestions and guidance.
Not able to connect keyvault in notebook in fabric
Hi Team, Hello Team, I am facing issue while connecting fabric with keyvault, getting below error client address is not authorized, and caller is not a trusted service.\r\nClient address: Earlier it was working fine, now started facing this.Please help Thanks
Connect to Lakehouse without MFA
HI Guys, I have a need to connect BrightGauge to Microsoft Lakehouse as an SQL connection. The problem is that BrightGauge cannot handle the modern authentication. Has anyone had luck connecting to a Lakehouse using legacy authentication database username and password?
Missing the option to create a fabric Lakehouse
Hi there, I am trying to follow some tutorials about the implementation of fabric and the creation of a lakehouse but for some reason I can only create an environment with my data engineering profile but no lakehouse. Any idea what I am missing here? I signed up for the 60 days fabric trial period.
TSQL vs Gen2 Dataflow
Hi, Will support be added soon to be able to write tables into a Lakehouse via T-SQL? I know it's possible for a Warehouse, but not yet for a Lakehouse. I've found that some queries are just 10x faster with T-SQL vs a Gen2 Dataflow, so I've been migrating over into T-SQL Views where possible (saving them in the SQL Endpoint environment). Trouble with Views is that you can't apply any ordering. That's only possible with Stored Procedures, and Stored procedures are only available so far with Warehouses. I'm not Spark SQL via a notebook since I don't like how you can't retain upper case naming on the Table names). Would be awesome to find out more!
