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DP-700試験の準備方法｜一番優秀なDP-700問題トレーリング試験｜素敵なImplementing Data Engineering Solutions Using Microsoft Fabric受験対策

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric 認定 DP-700 試験問題 (Q22-Q27):

質問 # 22
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 the join type to kind=outer.
Does this meet the goal?

A. Yes
B. No

正解：B

解説：
An outer join will include unmatched rows from both tables, increasing the dataset size and processing time. It does not improve query performance.

質問 # 23
You have five Fabric workspaces.
You are monitoring the execution of items by using Monitoring hub.
You need to identify in which workspace a specific item runs.
Which column should you view in Monitoring hub?

A. Activity name
B. Capacity
C. Job type
D. Location
E. Start time
F. Submitter
G. Item type

正解：D

解説：
To identify in which workspace a specific item runs in Monitoring hub, you should view the Location column. This column indicates the workspace where the item is executed. Since you have multiple workspaces and need to track the execution of items across them, the Location column will show you the exact workspace associated with each item or job execution.

質問 # 24
You need to create the product dimension.
How should you complete the Apache Spark SQL code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

Topic 2, Litware, Inc
Overview
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. is a publishing company that has an online bookstore and several retail bookstores worldwide. Litware also manages an online advertising business for the authors it represents.
Existing Environment. Fabric Environment
Litware has a Fabric workspace named Workspace1. High concurrency is enabled for Workspace1.
The company has a data engineering team that uses Python for data processing.
Existing Environment. Data Processing
The retail bookstores send sales data at the end of each business day, while the online bookstore constantly provides logs and sales data to a central enterprise resource planning (ERP) system.
Litware implements a medallion architecture by using the following three layers: bronze, silver, and gold. The sales data is ingested from the ERP system as Parquet files that land in the Files folder in a lakehouse. Notebooks are used to transform the files in a Delta table for the bronze and silver layers. The gold layer is in a warehouse that has V-Order disabled.
Litware has image files of book covers in Azure Blob Storage. The files are loaded into the Files folder.
Existing Environment. Sales Data
Month-end sales data is processed on the first calendar day of each month. Data that is older than one month never changes.
In the source system, the sales data refreshes every six hours starting at midnight each day.
The sales data is captured in a Dataflow Gen1 dataflow. When the dataflow runs, new and historical data is captured. The dataflow captures the following fields of the source:
Sales Date
Author
Price
Units
SKU
A table named AuthorSales stores the sales data that relates to each author. The table contains a column named AuthorEmail. Authors authenticate to a guest Fabric tenant by using their email address.
Existing Environment. Security Groups
Litware has the following security groups:
Sales
Fabric Admins
Streaming Admins
Existing Environment. Performance Issues
Business users perform ad-hoc queries against the warehouse. The business users indicate that reports against the warehouse sometimes run for two hours and fail to load as expected. Upon further investigation, the data engineering team receives the following error message when the reports fail to load: "The SQL query failed while running." The data engineering team wants to debug the issue and find queries that cause more than one failure.
When the authors have new book releases, there is often an increase in sales activity. This increase slows the data ingestion process.
The company's sales team reports that during the last month, the sales data has NOT been up-to-date when they arrive at work in the morning.
Requirements. Planned Changes
Litware recently signed a contract to receive book reviews. The provider of the reviews exposes the data in Amazon Simple Storage Service (Amazon S3) buckets.
Litware plans to manage Search Engine Optimization (SEO) for the authors. The SEO data will be streamed from a REST API.
Requirements. Version Control
Litware plans to implement a version control solution in Fabric that will use GitHub integration and follow the principle of least privilege.
Requirements. Governance Requirements
To control data platform costs, the data platform must use only Fabric services and items. Additional Azure resources must NOT be provisioned.
Requirements. Data Requirements
Litware identifies the following data requirements:
Process the SEO data in near-real-time (NRT).
Make the book reviews available in the lakehouse without making a copy of the data.
When a new book cover image arrives in the Files folder, process the image as soon as possible.

質問 # 25
HOTSPOT
You are processing streaming data from an external data provider.
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：

質問 # 26
You plan to process the following three datasets by using Fabric:
* Dataset1: This dataset will be added to Fabric and will have a unique primary key between the source and the destination. The unique primary key will be an integer and will start from 1 and have an increment of 1.
* Dataset2: This dataset contains semi-structured data that uses bulk data transfer. The dataset must be handled in one process between the source and the destination. The data transformation process will include the use of custom visuals to understand and work with the dataset in development mode.
* Dataset3. This dataset is in a takehouse. The data will be bulk loaded. The data transformation process will include row-based windowing functions during the loading process.
You need to identify which type of item to use for the datasets. The solution must minimize development effort and use built-in functionality, when possible. What should you identify for each dataset? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

質問 # 27
......

もしあなたはまだMicrosoftのDP-700試験に合格するのために悩まればTech4Examは今あなたを助けることができます。Tech4Examは高品質の学習資料をあなたを助けて優秀なMicrosoftのDP-700会員の認証を得て、もしあなたはMicrosoft DP-700の認証試験を通して自分を高めるの選択を下ろして、Tech4Examはとてもよい選択だと思います。

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有効なDP-700最新学習回答はあなたの考えをより明白にし、実用的なアプリケーションで問題を処理する能力を持っています、Microsoft DP-700問題トレーリングあなたがより良いなら、あなたはよりリラックスした生活を送るでしょう、どのようにMicrosoft DP-700試験を準備して、証明書を得ますか、勉強資料のメリット、Microsoft DP-700問題トレーリング弊社が提供した商品を利用すると試験にたやすく合格しました、したがって、当社のDP-700練習トレントはこれらの学習グループ向けにカスタマイズされているため、より生産的かつ効率的な方法で試験に合格し、職場で成功を収めることができます、DP-700試験準備の良い選択肢は、良い行動よりも重要な点があることを覚えておいてください。

ソフトフィルターのしきい値に合格した候補者の回答は仮説と証拠のスコアリングDP-700に入り、フィルターのしきい値に合格しなかった候補者は直接最終マージ段階に入ります、俺は、あいつの傷なんてどうでもいいよその言葉が本当だとは思えない。

DP-700問題トレーリングがImplementing Data Engineering Solutions Using Microsoft Fabricに合格するのを支援しましょう

有効なDP-700最新学習回答はあなたの考えをより明白にし、実用的なアプリケーションで問題を処理する能力を持っています、あなたがより良いなら、あなたはよりリラックスした生活を送るでしょう、どのようにMicrosoft DP-700試験を準備して、証明書を得ますか？

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