Microsoft Implementing Analytics Solutions Using Microsoft Fabric (DP-600日本語版) - DP-600日本語 Exam Questions

Explanation:
To identify the slowest DAX query and analyze the time it spends in the formula engine compared to the storage engine, you should perform the following actions in sequence:
From Performance analyzer, capture a recording.
View the Server Timings tab.
Enable Query Timings and Server Timings. Run the query.
View the Query Timings tab.
Sort the Duration (ms) column in descending order by DAX query time.

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Explanation:

The goal is to denormalize the data into a customer dimension with one row per distinct CustomerID, minimizing query processing time and resources. Since each customer is associated with a single SalesRegion and a single CustomerAddress, and all foreign key values are non-null, a left outer join is appropriate to ensure all customers from the Customer table are included, even if there are any unexpected missing addresses (though the problem states each customer has a single address). However, given the non-null foreign key constraint, an inner join could also work, but left outer join is safer and aligns with denormalization to ensure completeness.
The join condition should link the Customer table (C) with the CustomerAddress table (CA) using CustomerID, as this ensures each customer ' s address data is included.
The join with SalesRegion (SR) on SalesRegionID is already included in the query, and since each customer has a single SalesRegion, it fits the denormalization requirement.
The where CA.AddressType = ' Main Office ' filter ensures only the main office address is included, which is a valid constraint for a customer dimension.
Thus, the completed T-SQL statement would effectively denormalize the data while minimizing resource use by leveraging the existing relationships and constraints.

Explanation:

Scenario Recap
Fabric tenant # Workspace1
Contains:
Lakehouse LH1 (with table signindata in schema dho )
Warehouse DW1
Task: Create a stored procedure in DW1 that deduplicates rows in signindata .
Step 1: Stored procedure structure
In T-SQL, stored procedures begin with:
AS
BEGIN
-- logic
END
So the correct option for the first blank is BEGIN .
BEGIN DISTRIBUTED TRANSACTION is not needed because we are not spanning multiple servers or needing distributed transactions.
SET is not the right way to start the logic block.
Step 2: Deduplication logic
To remove duplicates from signindata , the query should return unique rows .
The simplest way is:
SELECT DISTINCT PersonID, FirstName, LastName
FROM dho.signindata;
Thus the correct choice for the second blank is DISTINCT .
GROUP BY could also deduplicate but is less efficient here since no aggregation is requested.
TOP 100 PERCENT WITH TIES is irrelevant.
Step 3: Final T-SQL stored procedure
CREATE PROCEDURE dbo.usp_GetPerson
AS
BEGIN
SELECT DISTINCT PersonID, FirstName, LastName
FROM dho.signindata;
END ;
Why this is correct
BEGIN # correct stored procedure structure.
DISTINCT # ensures deduplication of rows from signindata .
References
CREATE PROCEDURE (Transact-SQL)
DISTINCT (Transact-SQL)

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