DP-600 Exam Dumps - Implementing Analytics Solutions Using Microsoft Fabric

A replica of dbo.Sales is created in the test schema by copying the metadata only. - Yes

Additional schema changes to dbo.FactSales will also apply to test.FactSales. - No

Additional data changes to dbo.FactSales will also apply to test.FactSales. - No

The CREATE TABLE AS CLONE statement creates a copy of an existing table, including its data and any associated data structures, like indexes. Therefore, the statement does not merely copy metadata; it also copies the data. However, subsequent schema changes to the original table do not automatically propagate to the cloned table. Any data changes in the original table after the clone operation will not be reflected in the clone unless explicitly updated.

References =

CREATE TABLE AS SELECT (CTAS) in SQL Data Warehouse

When saving a semantic model to a file that can be edited using the Tabular Model Scripting Language (TMSL) extension for Visual Studio Code, the PBIX (Power BI Desktop) file format is the correct choice. The PBIX format contains the report, data model, and queries, and is the primary file format for editing in Power BI Desktop. References = Microsoft's documentation on Power BI file formats and Visual Studio Code provides further clarification on the usage of PBIX files.

The measure should use the AVERAGE function to calculate the average value.

It should reference the Response Value column from the 'Survey' table.

The 'Number of months' should be used to define the period for the average calculation.

To calculate the average overall satisfaction score using DAX, you would need to use the AVERAGE function on the response values related to satisfaction questions. The DATESINPERIOD function will help in calculating the rolling average over the last 12 months.

You should set Repeat for the schedule to Weekly (C). This allows you to specify the pipeline to run on specific days of the week, in this case, every four hours on Mondays and Fridays. References = Scheduling options for data pipelines are available in the Azure Data Factory documentation, which includes details on configuring recurring triggers.

Both a dataflow (A) and a Stored procedure activity in a pipeline (B) are capable of creating and populating a date dimension table. A dataflow can perform the transformation needed to create the date dimension, and it aligns with the preference for using low-code tools for data ingestion when possible. A Stored procedure could be written to generate the necessary date dimension data and executed within a pipeline, which also adheres to the technical requirements for the PoC.

You should use CREATE VIEW to make the pricing group logic available for T-SQL queries.

The CASE statement should be used to determine the pricing group based on the list price.

The T-SQL statement should create a view that classifies products into pricing groups based on the list price. The CASE statement is the correct conditional logic to assign each product to the appropriate pricing group. This view will standardize the pricing group logic across different databases and semantic models.