効果的なDP-700コンポーネント &合格スムーズDP-700日本語認定対策 |実際的なDP-700勉強方法

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Microsoft DP-700 認定試験の出題範囲:
| トピック | 出題範囲 |
|---|
| トピック 1 | - Implement and manage an analytics solution: This section of the exam measures the skills of Microsoft Data Analysts regarding configuring various workspace settings in Microsoft Fabric. It focuses on setting up Microsoft Fabric workspaces, including Spark and domain workspace configurations, as well as implementing lifecycle management and version control. One skill to be measured is creating deployment pipelines for analytics solutions.
|
| トピック 2 | - Ingest and transform data: This section of the exam measures the skills of Data Engineers that cover designing and implementing data loading patterns. It emphasizes preparing data for loading into dimensional models, handling batch and streaming data ingestion, and transforming data using various methods. A skill to be measured is applying appropriate transformation techniques to ensure data quality.
|
| トピック 3 | - Monitor and optimize an analytics solution: This section of the exam measures the skills of Data Analysts in monitoring various components of analytics solutions in Microsoft Fabric. It focuses on tracking data ingestion, transformation processes, and semantic model refreshes while configuring alerts for error resolution. One skill to be measured is identifying performance bottlenecks in analytics workflows.
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>> DP-700コンポーネント <<
DP-700日本語認定対策 & DP-700勉強方法
DP-700学習教材の練習試験や模擬試験はみんなにとって重要です。今のリビジョン条件はDP-700試験に参加する良い機会です。したがって、レビュープランを調整するために、DP-700の各練習問題を要約することが不可欠です。今、私たちはDP-700実際試験を模擬するためにオンラインテストエンジンとWindowsソフトウェアを追加しました。
Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric 認定 DP-700 試験問題 (Q95-Q100):
質問 # 95
You need to ensure that the data engineers are notified if any step in populating the lakehouses fails. The solution must meet the technical requirements and minimize development effort.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:
解説:

Explanation:

質問 # 96
You have an Azure event hub. Each event contains the following fields:
BikepointID
Street
Neighbourhood
Latitude
Longitude
No_Bikes
No_Empty_Docks
You need to ingest the events. The solution must only retain events that have a Neighbourhood value of Chelsea, and then store the retained events in a Fabric lakehouse.
What should you use?
- A. a KQL queryset
- B. a streaming dataset
- C. an eventstream
- D. Apache Spark Structured Streaming
正解:C
解説:
An eventstream is the best solution for ingesting data from Azure Event Hub into Fabric, while applying filtering logic such as retaining only the events that have a Neighbourhood value of "Chelsea." Eventstreams in Microsoft Fabric are designed for handling real-time data streams and can apply transformation logic directly on incoming events. In this case, the eventstream can filter events based on the Neighbourhood field before storing the retained events in a Fabric lakehouse.
Eventstreams are well-suited for stream processing, such as this case where you need to filter out only specific data (events with a Neighbourhood of "Chelsea") before storing it in the lakehouse.
質問 # 97
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a KQL database that contains two tables named Stream and Reference. Stream contains streaming data in the following format.

Reference contains reference data in the following format.

Both tables contain millions of rows.
You have the following KQL queryset.

You need to reduce how long it takes to run the KQL queryset.
Solution: You change project to extend.
Does this meet the goal?
正解:B
解説:
Using extend retains all columns in the table, potentially increasing the size of the output unnecessarily. project is more efficient because it selects only the required columns.
質問 # 98
You have the development groups shown in the following table.

You have the projects shown in the following table.

You need to recommend which Fabric item to use based on each development group ' s skillset The solution must meet the project requirements and minimize development effort What should you recommend for each group? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:
解説:

Explanation:

質問 # 99
You need to recommend a Fabric streaming solution that will use the sources shown in the following table.

The solution must minimize development effort.
What should you include in the recommendation for each source? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:
解説:

Explanation:

質問 # 100
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