DP-203資格取得 & DP-203絶対合格

ほとんどの労働者の基準はますます高くなっています。 DP-203ガイドの質問にも高い目標を設定しました。私たちのトレーニング資料は、顧客の関心を他のポイントよりも前面に置き、高度なDP-203学習資料に常に取り組んでいます。これまで、最も複雑なDP-203ガイドの質問を簡素化し、簡単な操作システムを設計しました。DP-203試験問題の自然でシームレスなユーザーインターフェイスは、より流fluentに成長しました。使いやすさ。

数年以来弊社のJpshikenのIT試験分野での研究を通して、弊社はこの職業での重要な存在になります。弊社の開発したソフトは非常に全面的です。MicrosoftのDP-203試験ソフトは販売量が一番高いソフトの一で、受験生をよく助けて受験生に試験に合格させます。知られているのはMicrosoftのDP-203試験に合格すればITという職業でよく発展しています。

>> DP-203資格取得 <<

効率的なDP-203資格取得 & 合格スムーズDP-203絶対合格 | 正確的なDP-203赤本合格率

一つには、当社の最も先進的なオペレーションシステムであり、最速の配信速度を保証でき、お客様の個人情報は弊社のオペレーションシステムによって自動的に暗号化されます。また、DP-203の実際の試験のオンラインアプリバージョンを使用すると、あらゆる種類の電子デバイスに関するトレーニング資料の質問を気軽に練習できます。さらに、DP-203試験問題の助けを借りて、お客様の合格率は98％〜100％に達しました。近い将来、あなたの学習パートナーになることを楽しみにしています。

Microsoft Data Engineering on Microsoft Azure 認定 DP-203 試験問題 (Q61-Q66):

質問 # 61
You have an Azure subscription that contains the resources shown in the following table.

You need to ingest the Parquet files from storage1 to SQL1 by using pipeline1. The solution must meet the following requirements:
* Minimize complexity.
* Ensure that additional columns in the files are processed as strings.
* Ensure that files containing additional columns are processed successfully.
How should you configure pipeline1? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

質問 # 62
You are creating an Azure Data Factory data flow that will ingest data from a CSV file, cast columns to specified types of data, and insert the data into a table in an Azure Synapse Analytic dedicated SQL pool. The CSV file contains three columns named username, comment, and date.
The data flow already contains the following:
A source transformation.
A Derived Column transformation to set the appropriate types of data.
A sink transformation to land the data in the pool.
You need to ensure that the data flow meets the following requirements:
All valid rows must be written to the destination table.
Truncation errors in the comment column must be avoided proactively.
Any rows containing comment values that will cause truncation errors upon insert must be written to a file in blob storage.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. To the data flow, add a filter transformation to filter out rows that will cause truncation errors.
B. Add a select transformation to select only the rows that will cause truncation errors.
C. To the data flow, add a Conditional Split transformation to separate the rows that will cause truncation errors.
D. To the data flow, add a sink transformation to write the rows to a file in blob storage.

正解：C、D

解説：
B: Example:
1. This conditional split transformation defines the maximum length of "title" to be five. Any row that is less than or equal to five will go into the GoodRows stream. Any row that is larger than five will go into the BadRows stream.

2. This conditional split transformation defines the maximum length of "title" to be five. Any row that is less than or equal to five will go into the GoodRows stream. Any row that is larger than five will go into the BadRows stream.
A:
3. Now we need to log the rows that failed. Add a sink transformation to the BadRows stream for logging. Here, we'll "auto-map" all of the fields so that we have logging of the complete transaction record. This is a text-delimited CSV file output to a single file in Blob Storage. We'll call the log file "badrows.csv".

4. The completed data flow is shown below. We are now able to split off error rows to avoid the SQL truncation errors and put those entries into a log file. Meanwhile, successful rows can continue to write to our target database.

Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-data-flow-error-rows

質問 # 63
You configure version control for an Azure Data Factory instance as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation
Letter Description automatically generated

Box 1: adf_publish
The Publish branch is the branch in your repository where publishing related ARM templates are stored and updated. By default, it's adf_publish.
Box 2: / dwh_batchetl/adf_publish/contososales
Note: RepositoryName (here dwh_batchetl): Your Azure Repos code repository name. Azure Repos projects contain Git repositories to manage your source code as your project grows. You can create a new repository or use an existing repository that's already in your project.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/source-control

質問 # 64
You implement an enterprise data warehouse in Azure Synapse Analytics.
You have a large fact table that is 10 terabytes (TB) in size.
Incoming queries use the primary key SaleKey column to retrieve data as displayed in the following table:

You need to distribute the large fact table across multiple nodes to optimize performance of the table.
Which technology should you use?

A. round robin distributed table with clustered Columnstore index
B. heap table with distribution replicate
C. hash distributed table with clustered Columnstore index
D. round robin distributed table with clustered index
E. hash distributed table with clustered index

正解：C

解説：
Hash-distributed tables improve query performance on large fact tables.
Columnstore indexes can achieve up to 100x better performance on analytics and data warehousing workloads and up to 10x better data compression than traditional rowstore indexes.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
https://docs.microsoft.com/en-us/sql/relational-databases/indexes/columnstore-indexes-query-performance

質問 # 65
Note: The 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 an Azure Data Lake Storage account that contains a staging zone.
You need to design a dairy process to ingest incremental data from the staging zone, transform the data by executing an R script, and then insert the transformed data into a data warehouse in Azure Synapse Analytics.
Solution: You use an Azure Data Factory schedule trigger to execute a pipeline that executes a mapping data low. and then inserts the data into the data warehouse.
Does this meet the goal?

A. Yes
B. No

正解：B

質問 # 66
......

DP-203試験を恐れることはありません。DP-203準備資料があなたの現在の生活を変えるのに役立つと信じています。 DP-203試験に合格して認定を取得できれば、近い将来新しい有意義な生活を始めることができます。したがって、DP-203模擬試験の準備をすることは非常に重要です。DP-203認定ガイドにもっと注意を払う必要があります。また、DP-203試験の質問は、認定を取得するためのすべての手助けとなります。

DP-203絶対合格: https://www.jpshiken.com/DP-203_shiken.html

Microsoft DP-203資格取得こうして、君は安心で試験の準備を行ってください、Microsoft DP-203資格取得時間はだれも待ちぬ古い諺があるように、試験の準備も同じです、Jpshiken のMicrosoftのDP-203問題集はシラバスに従って、それにDP-203認定試験の実際に従って、あなたがもっとも短い時間で最高かつ最新の情報をもらえるように、弊社はトレーニング資料を常にアップグレードしています、Microsoft DP-203資格取得実には、正確の方法と資料を探すなら、すべては問題ではりません、Jpshiken DP-203絶対合格を選ぶのは、成功を選ぶのに等しいと言えます。

と、思っていたりもする、ガイ・ユーは、彼は道徳的な懸念を打ち消すことがでDP-203絶対合格きますが、良い感情に欠けていますが、そのような場合でも、神の存在と来世を恐れさせるには十分です、こうして、君は安心で試験の準備を行ってください。

認定する-権威のあるDP-203資格取得試験-試験の準備方法DP-203絶対合格

時間はだれも待ちぬ古い諺があるように、試験の準備も同じです、Jpshiken のMicrosoftのDP-203問題集はシラバスに従って、それにDP-203認定試験の実際に従って、あなたがもっとも短い時間で最高かつ最新の情報をもらえるように、弊社はトレーニング資料を常にアップグレードしています。

実には、正確の方法と資料を探すなら、すべてDP-203は問題ではりません、Jpshikenを選ぶのは、成功を選ぶのに等しいと言えます。