NewValidDumpsのMicrosoftのDP-201受験記問題集を購入するなら、君がMicrosoftのDP-201受験記認定試験に合格する率は１００パーセントです。あなたはNewValidDumpsの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。MicrosoftのDP-201受験記認定試験に合格することはきっと君の職業生涯の輝い将来に大変役に立ちます。 NewValidDumpsを信じて、私たちは君のそばにいるから。NewValidDumpsの MicrosoftのDP-201受験記試験トレーニング資料はNewValidDumpsの実力と豊富な経験を持っているIT専門家が研究したもので、本物のMicrosoftのDP-201受験記試験問題とほぼ同じです。 購入した前の無料の試み、購入するときのお支払いへの保障、購入した一年間の無料更新MicrosoftのDP-201受験記試験に失敗した全額での返金…これらは我々のお客様への承諾です。

Azure Data Engineer Associate DP-201 できるだけ100％の通過率を保証使用にしています。

その中の一部は暇な時間だけでMicrosoftのDP-201 - Designing an Azure Data Solution受験記試験を準備します。 ただ、社会に入るIT卒業生たちは自分能力の不足で、DP-201 問題サンプル試験向けの仕事を探すのを悩んでいますか？それでは、弊社のMicrosoftのDP-201 問題サンプル練習問題を選んで実用能力を速く高め、自分を充実させます。その結果、自信になる自己は面接のときに、面接官のいろいろな質問を気軽に回答できて、順調にDP-201 問題サンプル向けの会社に入ります。

我々は尽力してあなたにMicrosoftのDP-201受験記試験に合格させます。あなたに安心にMicrosoftのDP-201受験記ソフトを購入させるために、我々は最も安全的な支払手段を提供します。PayPalは国際的に最大の安全的な支払システムです。

我々Microsoft DP-201受験記問題集を利用し、試験に参加しましょう。

多分、DP-201受験記テスト質問の数が伝統的な問題の数倍である。Microsoft　DP-201受験記試験参考書は全ての知識を含めて、全面的です。そして、DP-201受験記試験参考書の問題は本当の試験問題とだいたい同じことであるとわかります。DP-201受験記試験参考書があれば,ほかの試験参考書を勉強する必要がないです。

あなたはまだ躊躇しているなら、NewValidDumpsのDP-201受験記問題集デモを参考しましょ。なにごとによらず初手は难しいです、どのようにMicrosoft　DP-201受験記試験への復習を始めて悩んでいますか。

DP-201 PDF DEMO:

QUESTION NO: 1
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 are designing an HDInsight/Hadoop cluster solution that uses Azure Data Lake Gen1 Storage.
The solution requires POSIX permissions and enables diagnostics logging for auditing.
You need to recommend solutions that optimize storage.
Proposed Solution: Implement compaction jobs to combine small files into larger files.
Does the solution meet the goal?
A. Yes
B. No
Answer: A
Explanation
Depending on what services and workloads are using the data, a good size to consider for files is 256
MB or greater. If the file sizes cannot be batched when landing in Data Lake Storage Gen1, you can have a separate compaction job that combines these files into larger ones.
Note: POSIX permissions and auditing in Data Lake Storage Gen1 comes with an overhead that becomes apparent when working with numerous small files. As a best practice, you must batch your data into larger files versus writing thousands or millions of small files to Data Lake Storage Gen1.
Avoiding small file sizes can have multiple benefits, such as:
Lowering the authentication checks across multiple files
Reduced open file connections
Faster copying/replication
Fewer files to process when updating Data Lake Storage Gen1 POSIX permissions References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-best-practices

QUESTION NO: 2
You are planning a design pattern based on the Lambda architecture as shown in the exhibit.
Which Azure services should you use f2 or the cold path? To answer, drag the appropriate services to the correct layers. Each service 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.
Answer:
Explanation
Layer 2: Azure Data Lake Storage Gen2
Layer 3: Azure SQL Data Warehouse
Azure SQL Data Warehouse can be used for batch processing.
Note: Lambda architectures use batch-processing, stream-processing, and a serving layer to minimize the latency involved in querying big data.
References:
https://azure.microsoft.com/en-us/blog/lambda-architecture-using-azure-cosmosdb-faster- performance-low-tco-l
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch- processing

QUESTION NO: 3
You have a Windows-based solution that analyzes scientific data. You are designing a cloud- based solution that performs real-time analysis of the data.
You need to design the logical flow for the solution.
Which two actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Send data from the application to Azure Data Lake Storage.
B. Use an Azure Stream Analytics job in the cloud. Ingress data from an Azure Event Hub instance and build queries that output to Azure Data Lake Storage.
C. Use an Azure Stream Analytics job on an edge device. Ingress data from an Azure Data Factory instance and build queries that output to Power BI.
D. Send data from the application to an Azure Stream Analytics job.
E. Send data from the application to an Azure Event Hub instance.
F. Use an Azure Stream Analytics job in the cloud. Ingress data from the Azure Event Hub instance and build queries that output to Power BI.
Answer: E,F
Explanation
Stream Analytics has first-class integration with Azure data streams as inputs from three kinds of resources:
Azure Event Hubs
Azure IoT Hub
Azure Blob storage
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs

QUESTION NO: 4
You have an on-premises data warehouse that includes the following fact tables. Both tables have the following columns: DataKey, ProductKey, RegionKey. There are 120 unique product keys and 65 unique region keys.
Queries that use the data warehouse take a long time to complete.
You plan to migrate the solution to use Azure SQL Data Warehouse. You need to ensure that the
Azure-based solution optimizes query performance and minimizes processing skew.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation
Box 1: Hash-distributed
Box 2: ProductKey
ProductKey is used extensively in joins.
Hash-distributed tables improve query performance on large fact tables.
Box 3: Round-robin
Box 4: RegionKey
Round-robin tables are useful for improving loading speed.
Consider using the round-robin distribution for your table in the following scenarios:
* When getting started as a simple starting point since it is the default
* If there is no obvious joining key
* If there is not good candidate column for hash distributing the table
* If the table does not share a common join key with other tables
* If the join is less significant than other joins in the query
* When the table is a temporary staging table
Note: A distributed table appears as a single table, but the rows are actually stored across 60 distributions. The rows are distributed with a hash or round-robin algorithm.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute

QUESTION NO: 5
Which consistency level should you use for Health Interface?
A. Strong
B. Bounded Staleness
C. Session
D. Consistent Prefix
Answer: A
Explanation
Scenario: ADatum identifies the following requirements for the Health Interface application:
reads must display be the most recent committed version of an item.
Azure Cosmos DB consistency levels include:
Strong: Strong consistency offers a linearizability guarantee. Linearizability refers to serving requests concurrently. The reads are guaranteed to return the most recent committed version of an item. A client never sees an uncommitted or partial write. Users are always guaranteed to read the latest committed write.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels

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Updated: May 28, 2022