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| Section | Objectives |
|---|---|
| Real-time analytics | - Streaming and event processing
|
| Implement analytics solutions | - Data warehousing and modeling
|
| Get data into Microsoft Fabric | - Data ingestion and integration
|
| Implement data engineering solutions | - Lakehouse architecture
|
| Manage and secure Microsoft Fabric | - Governance and administration
|
DP-600パススルートレントの設計に多くの変更があります。 最も印象的なバージョンは、APPオンラインバージョンです。 通常、あらゆる種類のデジタルデバイスで使用できます。 しかし、オンラインではないときにオンラインバージョンを使用できるという特別な利点もあります。ネットワーク環境で初めて使用する場合は、どこからでもIt-PassportsのDP-600学習ガイドのオンラインバージョンを使用できます。 ネットワーク接続なし。 オンライン版のDP-600試験問題はあなたに適した選択肢だと思います
質問 # 116
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1 and a lakehouse named Lakehouse1. Warehouse1 contains a table named Table1.
Lakehouse1 contains a delta table named Table2.
You need to persist data from Table1 to Table2. The solution must use a low-code interface.
What should you do?
正解：C
解説：
To persist data from a Synapse Data Warehouse to a Lakehouse in Microsoft Fabric using a low- code approach, Dataflow Gen2 is the optimal tool. It provides a Power Query-based interface for data transformation and loading.
Reference:
https://www.waferwire.com/blog/create-tables-fabric-lakehouse
質問 # 117
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
Your network contains an on-premises Active Directory Domain Services (AD DS) domain named contoso.com that syncs with a Microsoft Entra tenant by using Microsoft Entra Connect.
You have a Fabric tenant that contains a semantic model.
You enable dynamic row-level security (RLS) for the model and deploy the model to the Fabric service.
You query a measure that includes the USERNAME() function, and the query returns a blank result.
You need to ensure that the measure returns the user principal name (UPN) of a user.
Solution: You update the measure to use the USEROBJECTID() function.
Does this meet the goal?
正解：A
質問 # 118
You have a Fabric warehouse that contains two tables named DimDate and Trips.
DimDate contains the following fields.
Trips contains the following fields.
You need to compare the average miles per trip for statutory holidays versus non-statutory holidays.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Comprehensive Detailed Explanation
Step 1: Requirement
We need to compare the average miles per trip for:
Statutory holidays (when IsHoliday = 1)
Non-statutory holidays (when IsHoliday = 0)
Step 2: Formula for average miles per trip
Average miles per trip = total miles ÷ number of trips
Total miles # SUM(t.tripDistance)
Number of trips # COUNT(t.tripID)
So the calculation is:
(SUM(t.tripDistance) / COUNT(t.tripID)) AS MilesPerTrip
Step 3: Grouping
We need a comparison by holiday status.
So we must group the results by:
GROUP BY d.IsHoliday
This ensures we get two rows: one for IsHoliday = 1 and one for IsHoliday = 0.
Step 4: Final Query
SELECT
d.IsHoliday,
(SUM(t.tripDistance) / COUNT(t.tripID)) AS MilesPerTrip
FROM DimDate d
INNER JOIN Trips t ON d.DateID = t.DateID
GROUP BY d.IsHoliday;
Why This is Correct
The formula ensures average miles per trip.
Grouping ensures comparison between holidays vs non-holidays.
Efficient aggregation, minimal computation.
References
Aggregate functions in T-SQL
GROUP BY clause
質問 # 119
You have a Fabric workspace that uses the default Spark starter pool and runtime version 1,2.
You plan to read a CSV file named Sales.raw.csv in a lakehouse, select columns, and save the data as a Delta table to the managed area of the lakehouse. Sales_raw.csv contains 12 columns.
You have the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
正解：
解説：
質問 # 120
You have a Fabric tenant that contains a data pipeline.
You need to ensure that the pipeline runs every four hours on Mondays and Fridays.
To what should you set Repeat for the schedule?
正解：D
解説：
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. Reference = Scheduling options for data pipelines are available in the Azure Data Factory documentation, which includes details on configuring recurring triggers.
質問 # 121
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