Microsoft DP-700受験料 & DP-700試験問題解説集

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Microsoft問題集では、オンラインでPDF、ソフトウェア、APPなど、3つのバージョンのDP-700ガイド資料を利用できます。最も人気のあるものは当社のDP-700試験問題のPDFバージョンであり、このバージョンの利便性を完全に楽しむことができます。これは主にデモがあるため、DP-700模擬試験の種類を選択するのに役立ちますあなたにふさわしく、正しい選択をします。 PDF版のDP-700学習資料を紙に印刷して、メモを書いたり強調を強調したりすることができます。

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
  • 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 2
  • 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.
トピック 3
  • 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.

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DP-700試験問題解説集 & DP-700試験解答

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric 認定 DP-700 試験問題 (Q139-Q144):

質問 # 139
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：


質問 # 140
You have a Google Cloud Storage (GCS) container named storage1 that contains the files shown in the following table.

You have a Fabric workspace named Workspace1 that has the cache for shortcuts enabled. Workspace1 contains a lakehouse named Lakehouse1. Lakehouse1 has the shortcuts shown in the following table.

You need to read data from all the shortcuts.
Which shortcuts will retrieve data from the cache?

正解：A

解説：
When reading data from shortcuts in Fabric (in this case, from a lakehouse like Lakehouse1), the cache for shortcuts helps by storing the data locally for quick access. The last accessed timestamp and the cache expiration rules determine whether data is fetched from the cache or from the source (Google Cloud Storage, in this case).
Products: The ProductFile.parquet was last accessed 12 hours ago. Since the cache has data available for up to
12 hours, it is likely that this data will be retrieved from the cache, as it hasn ' t been too long since it was last accessed.
Stores: The StoreFile.json was last accessed 4 hours ago, which is within the cache retention period.
Therefore, this data will also be retrieved from the cache.
Trips: The TripsFile.csv was last accessed 48 hours ago. Given that it ' s outside the typical caching window (assuming the cache has a maximum retention period of around 24 hours), it would not be retrieved from the cache. Instead, it will likely require a fresh read from the source.


質問 # 141
You need to ensure that the authors can see only their respective sales data.
How should you complete the statement? To answer, drag the appropriate values the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation:


質問 # 142
HOTSPOT
You are building a data loading pattern for Fabric notebook workloads.
You have the following code segment:

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 # 143
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：A

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 # 144
......

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