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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 Korean Version) Sample Questions:
Workspace라는 이름의 워크스페이스가 포함된 Fabric 테넌트가 있습니다! Workspace1은 Pro 라이선스 모드를 사용하며 Model1이라는 이름의 시맨틱 모델을 포함합니다.
Azure DevOps 조직을 보유하고 있습니다.
Workspace1에 대해 버전 관리를 활성화해야 합니다. 솔루션은 모델 1이 저장소에 추가되도록 해야 합니다.
어떤 세 가지 행동을 순서대로 수행해야 할까요? 정답을 선택하려면, 행동 목록에서 적절한 행동을 골라 답란에 옮겨 올바른 순서대로 배열하세요.
Correct Answer:
Explanation:
We need to enable version control for a Fabric workspace (Workspace1) and ensure that Model1 (a semantic model) is added to an Azure DevOps repository.
Key facts:
Workspace1 is in Pro mode. To enable Git integration, the workspace must be assigned to a Fabric capacity.
Git integration steps in Fabric:
Assign the workspace to a Fabric capacity.
Connect the workspace to a Git provider (e.g., Azure DevOps or GitHub).
Sync the workspace with the repository (to push artifacts like semantic models).
Branch policies and deployment pipelines are not needed for simply enabling version control.
Correct Sequence:
Assign Workspace1 to a Fabric capacity.
Connect Workspace1 to a Git provider.
Sync Workspace1 with the repository.
Final Answer:
Step 1 # Assign Workspace1 to a Fabric capacity
Step 2 # Connect Workspace1 to a Git provider
Step 3 # Sync Workspace1 with the repository
References:
Microsoft Fabric Git integration
Enable Git in Fabric workspace
This ensures Model1 will be version-controlled in the linked DevOps repository.
Workspace1이라는 이름의 Fabric 작업 영역과 storage라는 이름의 Azure Data Lake Storage Gen2 계정이 있습니다. Workspace1에는 Lakehouse1이라는 이름의 레이크하우스가 있습니다.
Lakehouse1에서 저장소 바로가기를 만들어야 합니다!
어떤 연결 및 엔드포인트를 지정해야 합니까? 답변하려면 답변 영역에서 적절한 옵션을 선택하십시오.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
When creating a shortcut to an Azure Data Lake Storage Gen2 account in a lakehouse, you should use the abfss (Azure Blob File System Secure) connection string and the dfs (Data Lake File System) endpoint. The abfss is used for secure access to Azure Data Lake Storage, and the dfs endpoint indicates that the Data Lake Storage Gen2 capabilities are to be used.
다음과 같은 KQL 쿼리가 있습니다.
다음 각 문장에 대해, 문장이 사실이면 '예'를 선택하고, 그렇지 않으면 '아니오'를 선택하십시오. 참고: 각 정답은 1점입니다.
Correct Answer:
Explanation:
We are analyzing this KQL query:
Sales
| where Status != " Cancelled "
| where OrderDate > = ago(30d)
| summarize TotalSales = sum(SalesAmount) by ProductCategory
| where TotalSales > 0
Statement 1:
" The query excludes sales that have a Status of Cancelled. "
Yes # where Status != " Cancelled " filters them out.
Statement 2:
" The query calculates the total sales of each product category for the last 30 days. " Yes # where OrderDate > = ago(30d) ensures only last 30 days.
summarize TotalSales = sum(SalesAmount) by ProductCategory groups by category.
Statement 3:
" The query includes product categories that have had zero sales during the last 30 days. " No # The final filter where TotalSales > 0 excludes categories with zero sales.
Final Answer:
Excludes Cancelled sales # Yes
Calculates total sales by product category for last 30 days # Yes
Includes product categories with zero sales # No
References:
KQL where operator
KQL summarize operator
현재 Fabric 테넌트에는 model1이라는 이름의 시맨틱 모델이 있습니다. model1에서 가장 큰 두 개의 열은 다음 표에 나와 있습니다.
모델 1을 최적화해야 합니다. 최적화 결과는 다음 요구 사항을 충족해야 합니다.
* 모델 크기를 줄이세요.
* 가져오기 모드 사용 시 새로 고침 성능을 향상시킵니다.
* 각 판매 거래에 대한 날짜 및 시간 값이 모델에 포함되어 있는지 확인하십시오.
각 열에서 무엇을 해야 할까요? 정답을 선택하려면 답변란에서 적절한 옵션을 고르세요.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
We are optimizing model1 in Fabric with two very large columns:
TransactionKey
Cardinality: 2.5 billion
Size: 160 GB
Description: surrogate key for SalesTransaction fact table.
SaleDateTime
Cardinality: 6.8 million
Size: 120 GB
Description: datetime (to the second) of when a sale occurred.
Goal:
Reduce model size.
Improve refresh performance (Import mode).
Ensure datetime values remain available.
Analysis per column
1. TransactionKey (very high cardinality)
Surrogate keys with extremely high cardinality do not add analytical value in a semantic model because they are not used in measures or grouping.
They take a lot of memory and reduce refresh performance.
Best practice: remove the column from the model.
2. SaleDateTime
Needed to analyze transactions by date and time.
However, storing the full datetime at second-level cardinality causes huge memory usage.
To optimize: split the column into Date and Time columns.
Reduces cardinality significantly.
Preserves full datetime information (can recombine if needed).
Improves compression and refresh speed.
Final Answer:
TransactionKey: Remove the column.
SaleDateTime: Split the column.
References:
Microsoft Fabric optimization guidance - reduce cardinality
Best practices for datetime optimization in semantic models
# Answer Selection:
TransactionKey # Remove the column
SaleDateTime # Split the column
귀사는 호숫가 주택 두 채를 소유한 Fabric 임차인을 보유하고 있습니다.
호숫가 주택들의 데이터를 결합하는 데이터플로우를 구축하고 있습니다. 데이터플로우의 쿼리 중 하나에 적용된 단계는 다음 그림에 나와 있습니다.
아래 그림에 제시된 정보를 바탕으로 각 문장을 완성하는 답을 드롭다운 메뉴에서 선택하세요. 참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
Folding in Power Query refers to operations that can be translated into source queries. In this case, " some " of the steps can be folded, which means that some transformations will be executed at the data source level. The steps that cannot be folded will be executed within the Power Query engine. Custom steps, especially those that are not standard query operations, are usually executed within Power Query engine rather than being pushed down to the source system.
References =
Query folding in Power Query
Power Query M formula language
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