Explanation:
* Remove the files: Run the VACUUM command on a schedule.
* Combine the files: Set the optimizeWrite table setting. or Run the OPTIMIZE command on a schedule.
To remove files that are no longer used, the VACUUM command is used in Delta Lake to clean up invalid files from a table. To combine smaller files into larger ones, you can either set the optimizeWrite setting to combine files during write operations or use the OPTIMIZE command, which is a Delta Lake operation used to compact small files into larger ones.

Power BI, Create dynamic format strings for measures
With dynamic format strings for measures, you can determine how measures appear in visuals by conditionally applying a format string with a separate DAX expression.
A common scenario with financial reports is showing the currency converted to other country currencies by multiplying the base currency by an exchange rate. This also takes advantage of the dynamic format strings of calculation items to show the converted currency also in the correct currency format. Calculation items can have the conversion DAX expression defined once that can be applied to the many measures in the model showing currency values, without the need to edit or duplicate many measures.
Reference:
https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-dynamic-format-strings
https://powerbi.microsoft.com/en-us/blog/deep-dive-into-the-model-explorer-with-calculation- group-authoring-and-creating-relationships-in-the-properties-pane/

Explanation:

You need to configure OneLake security for two users with the following requirements:
User1: Read all the Spark data
User2: Read all the SQL endpoint data
The available permissions are: Read, ReadAll, and ReadData.
Understanding the permissions:
Read # Grants access to metadata but not the data itself.
ReadData # Grants access to query data through SQL endpoints (SQL-based access).
ReadAll # Grants access to read data across all engines (including Spark and SQL endpoints).
Applying least privilege principle:
User1 (Spark access): Needs to read all the Spark data # Assign ReadAll because Spark requires this permission to access data in OneLake.
User2 (SQL endpoint access): Needs to read SQL endpoint data only # Assign ReadData, as this grants access to SQL endpoints without over-provisioning Spark access.
Final Answer:
User1: ReadAll
User2: ReadData
References:
Microsoft Fabric OneLake permissions
Fabric Lakehouse & SQL Endpoint security

The transformation you should select from the context menu of the VendorID column to transform the date columns into attribute-value pairs, where columns become rows, is Unpivot columns (B). This transformation will turn the selected columns into rows with two new columns, one for the attribute (the original column names) and one for the value (the data from the cells). Reference = Techniques for unpivoting columns are covered in the Power Query documentation, which explains how to use the transformation in data modeling.

To ensure read-write access to DS1 is available by using the XMLA endpoint, the C1 settings (which refer to the capacity settings) should be modified first. XMLA endpoint configuration is a capacity feature, not specific to individual datasets or workspaces. References = The configuration of XMLA endpoints in Power BI capacities is detailed in the Power BI documentation on dataset management.