Exam Name: Implementing Analytics Solutions Using Microsoft Fabric (DP-600日本語版)
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Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-600
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Microsoft Implementing Analytics Solutions Using Microsoft Fabric (DP-600日本語版) Sample Questions:
Fabricワークスペースには、Warehouse!という名前の倉庫が含まれています。Warehouse!には、次のデータが含まれています。
テーブルを非正規化し、結果に ContractType 属性と StartDate 属性を含める T-SQL ステートメントを作成する必要があります。ソリューションは以下の要件を満たす必要があります。
* 契約テーブルの該当する行から属性を含める。
* 従業員テーブルのすべての行が保持されていることを確認してください。
* 従業員が2人を超えるすべての契約タイプについて、契約タイプごとの従業員総数を返します。
この文をどのように完成させればよいでしょうか？回答するには、回答欄で適切な選択肢を選んでください。
注：正解ごとに1ポイントが加算されます。
Correct Answer:
Explanation:
Comprehensive Detailed Explanation
We are tasked with writing a T-SQL query to denormalize the tables Employee and Contract in a Fabric warehouse.
Requirements Breakdown
Include attributes from matching rows in the Contract table
This means we must join Employee and Contract on EmployeeID.
Ensure that all rows from the Employee table are preserved
This requires a LEFT OUTER JOIN from Employee to Contract. If an employee has no contract, we still want the employee record included.
Return the total number of employees per contract type for all contract types that have more than two employees This means we need to:
Group by ContractType
Count distinct EmployeeID
Filter groups where that count > 2.
To filter aggregated results, we use HAVING, not WHERE.
Completed Query
WITH result AS (
SELECT
e.EmployeeID,
e.EmployeeName,
e.EmployeePosition,
c.ContractType,
c.StartDate
FROM Employee AS e
LEFT OUTER JOIN Contract AS c
ON c.EmployeeID = e.EmployeeID
)
SELECT
ContractType,
COUNT(DISTINCT EmployeeID) AS TotalEmployees
FROM result
GROUP BY ContractType
HAVING COUNT(DISTINCT EmployeeID) > 2;
Why This is Correct
LEFT OUTER JOIN ensures all employees are included, regardless of contracts.
HAVING allows filtering aggregated groups by employee counts.
The query returns ContractType, StartDate (as requested in denormalization), and aggregated employee counts.
References
T-SQL JOINs in Microsoft Fabric
Aggregate functions and HAVING clause
Denormalization best practices in Fabric warehouses
Fabricワークスペース「Workspace1」には、「Dataflow1」という名前のデータフローが含まれています。Dataflow1には、次の図に示すデータを返すクエリが含まれています。
日付列を属性と値のペアに変換する必要があります。つまり、列が行になります。
「VendorlD」列を選択します。
VendorlD列のコンテキストメニューから、どの変換を選択すればよいですか？
- A. グループ化
- B. 分割列
- C. 他の列のピボットを解除する
- D. 他の列を削除する
- E. 列のピボット解除
Correct Answer: C 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
セマンティックモデルを含むFabricテナントをお持ちです。このモデルには、小売店に関するデータが含まれています。
XMLAエンドポイントを使用して実行されるDAXクエリを作成する必要があります。このクエリは、前年同期の売上合計額を返す必要があります。
DAX式をどのように完成させるべきですか？回答するには、回答欄で適切なオプションを選択してください。
注：正解ごとに1ポイントが加算されます。
Correct Answer:
Explanation:
First blank: CALCULATE
Second blank: _LYSales
Step 1 - Defining the variable
We want to calculate sales for the same period in the prior year. The correct function here is CALCULATE, because it allows applying a filter context modification (with SAMEPERIODLASTYEAR).
So:
VAR _LYSales =
CALCULATE ( [Total Sales], SAMEPERIODLASTYEAR ( ' Orders ' [Order Date] ) ) Step 2 - Returning the value We then need to RETURN the value of the variable. From the dropdown options, we select _LYSales.
So:
EVALUATE
VAR _LYSales =
CALCULATE ( [Total Sales], SAMEPERIODLASTYEAR ( ' Orders ' [Order Date] ) ) RETURN ROW ( " LastYearSales " , _LYSales ) Note: In XMLA DAX queries, you usually need a table expression, so wrapping with ROW or SELECTCOLUMNS is common, but based on the provided answer box, just returning _LYSales is sufficient here.
Final Answer:
First blank: CALCULATE
Second blank: _LYSales
Fabricテナントには、lakehouse1という名前の湖畔の家が含まれています。lakehouse1には、Table1という名前のパーティション化されていないテーブルが含まれています。
あなたは、データをTable1にコピーし、ソースデータの日付列に基づいてテーブルをパーティション分割することを計画しています。
データをTable1にコピーするためのコピーアクティビティを作成します。
コピーアクティビティの宛先設定で、パーティション列を指定する必要があります。
まず最初に何をすべきでしょうか？
- A. [宛先]タブからパーティション列を選択します。
- B. [宛先]タブから、[モード]を[追加]に設定します。
- C. [ソース]タブから[パーティション検出を有効にする]を選択します。
- D. [宛先]タブから、[モード]を[上書き]に設定します。
Correct Answer: D 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
definition.pbir という名前のファイルを含む Microsoft Power BL プロジェクトがあります。 definition.pbir には次の JSON が含まれています。
以下の各設問について、該当する場合は「はい」を選択してください。該当しない場合は「いいえ」を選択してください。注：正解ごとに1点が加算されます。
Correct Answer:
Explanation:
We are analyzing the JSON for definition.pbir in a Power BI Project:
{
" version " : " 1.0 " ,
" datasetReference " : {
" byPath " : {
" path " : " ../Sales.Dataset "
},
" byConnection " : null
}
}
Statement 1:
" definition.pbir is in the PBIR-Legacy format. "
No # The legacy PBIR format references datasets by byConnection (pointing to the Power BI service).
Here, it uses byPath, which is the new project format, not legacy.
Statement 2:
" The semantic model referenced by definition.pbir is located in the Power BI service. " No # The JSON shows byPath: " ../Sales.Dataset " , meaning the semantic model is referenced locally within the project folder (Sales.Dataset), not in the Power BI service.
Statement 3:
" When the related report is opened, Power BI Desktop will open the semantic model in full edit mode. " Yes # Since the semantic model is referenced by path (local PBIP project files), Power BI Desktop will open the model in full edit mode. If it had been byConnection, it would open in live connect mode to the service instead.
Final Answer:
PBIR-Legacy format # No
Semantic model in Power BI service # No
Opens in full edit mode # Yes
References:
Power BI Project (PBIP) structure
PBIR formats: byPath vs byConnection
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