多くの時間とお金がいらなくて２０時間だけあって楽に一回にMicrosoftのDP-200模擬解説集認定試験を合格できます。NewValidDumpsが提供したMicrosoftのDP-200模擬解説集試験問題と解答が真実の試験の練習問題と解答は最高の相似性があります。 あなたはキャリアで良い昇進のチャンスを持ちたいのなら、NewValidDumpsのMicrosoftのDP-200模擬解説集「Implementing an Azure Data Solution」試験トレーニング資料を利用してMicrosoftの認証の証明書を取ることは良い方法です。現在、MicrosoftのDP-200模擬解説集認定試験に受かりたいIT専門人員がたくさんいます。 でもNewValidDumpsの最新問題集がこの問題を解決できますよ。

MicrosoftのDP-200模擬解説集試験は挑戦がある認定試験です。

うちのMicrosoftのDP-200 - Implementing an Azure Data Solution模擬解説集試験トレーニング資料を購入する前に、NewValidDumpsのサイトで、一部分のフリーな試験問題と解答をダンロードでき、試用してみます。 それに、我々は一年間の無料更新サービスを提供します。失敗しましたら、当社は全額で返金して、あなたの利益を保障します。

我々の誠意を信じてください。あなたが順調に試験に合格するように。時間とお金の集まりより正しい方法がもっと大切です。

Microsoft DP-200模擬解説集 - あなたもIT認証資格を取りたいですか。

世の中に去年の自分より今年の自分が優れていないのは立派な恥です。それで、IT人材として毎日自分を充実して、DP-200模擬解説集問題集を学ぶ必要があります。弊社のDP-200模擬解説集問題集はあなたにこのチャンスを全面的に与えられます。あなたは自分の望ましいMicrosoft DP-200模擬解説集問題集を選らんで、学びから更なる成長を求められます。心はもはや空しくなく、生活を美しくなります。

試験問題集が更新されると、NewValidDumpsは直ちにあなたのメールボックスにDP-200模擬解説集問題集の最新版を送ります。あなたは試験の最新バージョンを提供することを要求することもできます。

DP-200 PDF DEMO:

QUESTION NO: 1
A company builds an application to allow developers to share and compare code. The conversations, code snippets, and links shared by people in the application are stored in a Microsoft
Azure SQL Database instance.
The application allows for searches of historical conversations and code snippets.
When users share code snippets, the code snippet is compared against previously share code snippets by using a combination of Transact-SQL functions including SUBSTRING, FIRST_VALUE, and
SQRT. If a match is found, a link to the match is added to the conversation.
Customers report the following issues:
* Delays occur during live conversations
* A delay occurs before matching links appear after code snippets are added to conversations You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology 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
Box 1: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view

QUESTION NO: 2
You are implementing automatic tuning mode for Azure SQL databases.
Automatic tuning is configured as shown in the following table.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Automatic tuning options can be independently enabled or disabled per database, or they can be configured on SQL Database servers and applied on every database that inherits settings from the server. SQL Database servers can inherit Azure defaults for Automatic tuning settings. Azure defaults at this time are set to FORCE_LAST_GOOD_PLAN is enabled, CREATE_INDEX is enabled, and
DROP_INDEX is disabled.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-automatic-tuning

QUESTION NO: 3
You develop data engineering solutions for a company. You must migrate data from
Microsoft Azure Blob storage to an Azure SQL Data Warehouse for further transformation. You need to implement the solution.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation
Step 1: Provision an Azure SQL Data Warehouse instance.
Create a data warehouse in the Azure portal.
Step 2: Connect to the Azure SQL Data warehouse by using SQL Server Management Studio Connect to the data warehouse with SSMS (SQL Server Management Studio) Step 3: Build external tables by using the SQL Server Management Studio Create external tables for data in Azure blob storage.
You are ready to begin the process of loading data into your new data warehouse. You use external tables to load data from the Azure storage blob.
Step 4: Run Transact-SQL statements to load data.
You can use the CREATE TABLE AS SELECT (CTAS) T-SQL statement to load the data from Azure
Storage Blob into new tables in your data warehouse.
References:
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/sql-data-warehouse/load-data- from-azure-blob

QUESTION NO: 4
You manage an enterprise data warehouse in Azure Synapse Analytics.
Users report slow performance when they run commonly used queries. Users do not report performance changes for infrequently used queries.
You need to monitor resource utilization to determine the source of the performance issues.
Which metric should you monitor?
A. DWU limit
B. Data Warehouse Units (DWU) used
C. Data IO percentage
D. Cache hit percentage
Answer: D
Explanation
The Azure Synapse Analytics storage architecture automatically tiers your most frequently queried columnstore segments in a cache residing on NVMe based SSDs designed for Gen2 data warehouses.
Greater performance is realized when your queries retrieve segments that are residing in the cache.
You can monitor and troubleshoot slow query performance by determining whether your workload is optimally leveraging the Gen2 cache.
Note: As of November 2019, Azure SQL Data Warehouse is now Azure Synapse Analytics.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-how-to-monitor- cache
https://docs.microsoft.com/bs-latn-ba/azure/sql-data-warehouse/sql-data-warehouse-concept- resource-utilization

QUESTION NO: 5
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 scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
* A workload for data engineers who will use Python and SQL
* A workload for jobs that will run notebooks that use Python, Spark, Scala, and SQL
* A workload that data scientists will use to perform ad hoc analysis in Scala and R The enterprise architecture team at your company identifies the following standards for Databricks environments:
* The data engineers must share a cluster.
* The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
* All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databrick clusters for the workloads.
Solution: You create a High Concurrency cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?
A. No
B. Yes
Answer: A
Explanation
No need for a High Concurrency cluster for each data scientist.
Standard clusters are recommended for a single user. Standard can run workloads developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
References:
https://docs.azuredatabricks.net/clusters/configure.html

短時間でNetSuite SuiteFoundation試験に一発合格したいなら、我々社のMicrosoftのNetSuite SuiteFoundation資料を参考しましょう。 Salesforce Marketing-Cloud-Account-Engagement-Consultant-JPN - 問題集に含まれているものは実際試験の問題を全部カバーすることができますから、あなたが一回で成功することを保証できます。 人によって目標が違いますが、あなたにMicrosoft　Amazon Data-Engineer-Associate-KR試験に順調に合格できるのは我々の共同の目標です。 うちのMicrosoftのCisco 700-826学習教材はNewValidDumpsのIT専門家たちが研究して、実践して開発されたものです。 あなたに高品質で、全面的なSalesforce Salesforce-Sales-Representative参考資料を提供することは私たちの責任です。

Updated: May 28, 2022