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Microsoft DP-600 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Prepare data: This section of the exam measures the skills of engineers and covers essential data preparation tasks. It includes establishing data connections and discovering sources through tools like the OneLake data hub and the real-time hub. Candidates must demonstrate knowledge of selecting the appropriate storage type—lakehouse, warehouse, or eventhouse—depending on the use case. It also includes implementing OneLake integrations with Eventhouse and semantic models. The transformation part involves creating views, stored procedures, and functions, as well as enriching, merging, denormalizing, and aggregating data. Engineers are also expected to handle data quality issues like duplicates, missing values, and nulls, along with converting data types and filtering. Furthermore, querying and analyzing data using tools like SQL, KQL, and the Visual Query Editor is tested in this domain.
トピック 2	Implement and manage semantic models: This section of the exam measures the skills of architects and focuses on designing and optimizing semantic models to support enterprise-scale analytics. It evaluates understanding of storage modes and implementing star schemas and complex relationships, such as bridge tables and many-to-many joins. Architects must write DAX-based calculations using variables, iterators, and filtering techniques. The use of calculation groups, dynamic format strings, and field parameters is included. The section also includes configuring large semantic models and designing composite models. For optimization, candidates are expected to improve report visual and DAX performance, configure Direct Lake behaviors, and implement incremental refresh strategies effectively.
トピック 3	Maintain a data analytics solution: This section of the exam measures the skills of administrators and covers tasks related to enforcing security and managing the Power BI environment. It involves setting up access controls at both workspace and item levels, ensuring appropriate permissions for users and groups. Row-level, column-level, object-level, and file-level access controls are also included, alongside the application of sensitivity labels to classify data securely. This section also tests the ability to endorse Power BI items for organizational use and oversee the complete development lifecycle of analytics assets by configuring version control, managing Power BI Desktop projects, setting up deployment pipelines, assessing downstream impacts from various data assets, and handling semantic model deployments using XMLA endpoint. Reusable asset management is also a part of this domain.

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もし弊社のMicrosoftのDP-600「Implementing Analytics Solutions Using Microsoft Fabric」認証試験について問題集に興味があったら、購入するまえにインターネットで弊社が提供した無料な部分問題集をダウンロードして、君の試験に役に立つかどうかのを自分が判断してください。それにPass4Testは一年の無料な更新のサービスを提供いたします。

Microsoft Implementing Analytics Solutions Using Microsoft Fabric 認定 DP-600 試験問題 (Q33-Q38):

質問 # 33
You have a Fabric tenant.
You are creating a Fabric Data Factory pipeline.
You have a stored procedure that returns the number of active customers and their average sales for the current month.
You need to add an activity that will execute the stored procedure in a warehouse. The returned values must be available to the downstream activities of the pipeline.
Which type of activity should you add?

A. Append variable
B. Stored procedure
C. Script
D. Get metadata

正解：B

質問 # 34
You have a Fabric warehouse that contains a table named Sales.Orders. Sales.Orders contains the following columns.

You need to write a T-SQL query that will return the following columns.

How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation:

For the PeriodDate that returns the first day of the month for OrderDate, you should use DATEFROMPARTS as it allows you to construct a date from its individual components (year, month, day).
For the DayName that returns the name of the day for OrderDate, you should use DATENAME with the weekday date part to get the full name of the weekday.
The complete SQL query should look like this:
SELECT OrderID, CustomerID,
DATEFROMPARTS(YEAR(OrderDate), MONTH(OrderDate), 1) AS PeriodDate,
DATENAME(weekday, OrderDate) AS DayName
FROM Sales.Orders
Select DATEFROMPARTS for the PeriodDate and weekday for the DayName in the answer area.

質問 # 35
You have a Fabric tenant that contains a data warehouse named DW1. DW1 contains a table named DimCustomer. DimCustomer contains the fields shown in the following table.

You need to identify duplicate email addresses in DimCustomer. The solution must return a maximum of
1,000 records.
Which four T-SQL statements should you run in sequence? To answer, move the appropriate statements from the list of statements to the answer area and arrange them in the correct order.

正解：

解説：

Explanation:

Step 1 - Select the required fields and count
We want to group by CustomerAltKey and count occurrences.
SELECT CustomerAltKey, COUNT ( * )
Step 2 - From the table
FROM DimCustomer
Step 3 - Grouping by email
GROUP BY CustomerAltKey
Step 4 - Filtering duplicates (only values with count > 1)
HAVING COUNT ( * ) > 1
Step 5 - Limiting the result to 1,000 rows
LIMIT 1000
(or in T-SQL, SELECT TOP(1000) ... ). Since both options are shown, we use LIMIT 1000 because Fabric Warehouse supports Synapse SQL T-SQL + ANSI SQL style.
Correct Sequence:
SELECT CustomerAltKey, COUNT(*)
FROM DimCustomer
GROUP BY CustomerAltKey
HAVING COUNT(*) > 1
LIMIT 1000

質問 # 36
You have the following T-SQL statement.

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：

Explanation:

質問 # 37
You have a Fabric workspace named Workspace1 that contains a data flow named Dataflow1. Dataflow1 contains a query that returns the data shown in the following exhibit.

You need to transform the date columns into attribute-value pairs, where columns become rows.
You select the VendorlD column.
Which transformation should you select from the context menu of the VendorlD column?

A. Split column
B. Unpivot columns
C. Group by
D. Remove other columns
E. Unpivot other columns

正解：E

解説：
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). References = Techniques for unpivoting columns are covered in the Power Query documentation, which explains how to use the transformation in data modeling.

質問 # 38
......

これらすべてのDP-600学習教材で、あなたの成功は100％保証されます。さらに、無料のデモがあります。無料のデモでは、練習資料の内容について証明された経験に基づいた推測を提供します。 DP-600試験の知識を、あなたのように成功することに熱心な熱心な試験受験者に伝えることで、彼らはそれを助けを提供する責任として扱います。あなたの情報の次の特徴を備えたDP-600学習ガイドを入手できる場合は、驚くべき進歩を遂げる準備をしてください。

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