The display function is the correct choice to make the data available in the Chart view within a Fabric notebook. This function is used to visualize Spark DataFrames in various formats including charts and graphs directly within the notebook environment. References = Further explanation of the display function can be found in the official documentation on Azure Synapse Analytics notebooks.

Explanation:

The Spark engine will read only the 'SalesOrderNumber', 'OrderDate', 'CustomerName', 'UnitPrice' columns from Sales_raw.csv. - Yes Removing the partition will reduce the execution time of the query. - No Adding inferSchema='true' to the options will increase the execution time of the query. - Yes The code specifies the selection of certain columns, which means only those columns will be read into the DataFrame. Partitions in Spark are a way to optimize the execution of queries by organizing the data into parts that can be processed in parallel. Removing the partition could potentially increase the execution time because Spark would no longer be able to process the data in parallel efficiently. The inferSchema option allows Spark to automatically detect the column data types, which can increase the execution time of the initial read operation because it requires Spark to read through the data to infer the schema.

For a Type 1 SCD, you should include actions that update rows when non-key attributes have changed (A), and insert new records when the natural key is a new value in the table (D). A Type 1 SCD does not track historical data, so you always overwrite the old data with the new data for a given key. References = Details on Type 1 slowly changing dimension patterns can be found in data warehousing literature and Microsoft's official documentation.

In Microsoft Fabric, a shortcut lets you reference data from another workspace's Lakehouse or external storage without duplicating the data.
A view would only apply within the same database/Lakehouse, not across workspaces.
A dataflow transforms and loads data but creates a new copy.
A managed table is a physical table stored in the Lakehouse itself, not a cross-reference.
So, to query dbo.Sales (Lakehouse1) and dbo.Customers (Lakehouse2) in a single SQL query, you use shortcuts.
Reference: Shortcuts in OneLake

Comprehensive Detailed Explanation
Requirement
We have two columns in Power Query Editor:
Order_Date
Shipping_Date
We need to calculate the number of days between the two dates.
Step 1: How date differences work in Power Query (M language)
Subtracting two date or datetime values in Power Query returns a duration value.
Example:
[Shipping_Date] - [Order_Date]
This produces a duration such as 3.00:00:00 (3 days).
Step 2: Converting duration into days
To get the number of days as an integer, we use Duration.Days().
Example:
Duration.Days([Shipping_Date] - [Order_Date])
This returns 3 if the shipping date is 3 days after the order date.
Step 3: Evaluate other options
A). Duration.From # Converts a value to a duration type but does not extract the number of days.
B). Date.AddDays # Adds days to a given date, not used for calculating the difference.
C). Duration.Days # Correct, extracts total days from a duration.
D). DateTime.LocalNow # Returns the current system datetime, unrelated to this requirement.
References
Duration.Days function (Power Query M)
Working with dates in Power Query