NewValidDumpsの専門家チームが君の需要を満たすために自分の経験と知識を利用してMicrosoftのDP-200的中合格問題集認定試験対策模擬テスト問題集が研究しました。模擬テスト問題集と真実の試験問題がよく似ています。一目でわかる最新の出題傾向でわかりやすい解説と充実の補充問題があります。 これは心のヘルプだけではなく、試験に合格することで、明るい明日を持つこともできるようになります。IT認証試験に合格したい受験生の皆さんはきっと試験の準備をするために大変悩んでいるでしょう。 NewValidDumpsのMicrosoftのDP-200的中合格問題集の試験問題は同じシラバスに従って、実際のMicrosoftのDP-200的中合格問題集認証試験にも従っています。

Azure Data Engineer Associate DP-200 あなたは最高のトレーニング資料を手に入れました。

Azure Data Engineer Associate DP-200的中合格問題集 - Implementing an Azure Data Solution IT認証は同業種の欠くことができないものになりました。 」このような考えがありますか。しかし、どのようにより良い仕事を行うことができますか。

NewValidDumpsに会ったら、最高のトレーニング資料を見つけました。NewValidDumpsのMicrosoftのDP-200的中合格問題集試験トレーニング資料を持っていたら、試験に対する充分の準備がありますから、安心に利用したください。NewValidDumpsは優れたIT情報のソースを提供するサイトです。

Microsoft DP-200的中合格問題集 - 不思議でしょう。

DP-200的中合格問題集認定試験に合格することは難しいようですね。試験を申し込みたいあなたは、いまどうやって試験に準備すべきなのかで悩んでいますか。そうだったら、下記のものを読んでください。いまDP-200的中合格問題集試験に合格するショートカットを教えてあげますから。あなたを試験に一発合格させる素晴らしいDP-200的中合格問題集試験に関連する参考書が登場しますよ。それはNewValidDumpsのDP-200的中合格問題集問題集です。気楽に試験に合格したければ、はやく試しに来てください。

NewValidDumpsは君が最も早い時間でMicrosoftのDP-200的中合格問題集試験に合格するのを助けます。私たちは君がITエリートになるのに頑張ります。

DP-200 PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
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

QUESTION NO: 4
You have a table named SalesFact in an Azure SQL data warehouse. SalesFact contains sales data from the past 36 months and has the following characteristics:
* Is partitioned by month
* Contains one billion rows
* Has clustered columnstore indexes
All the beginning of each month, you need to remove data SalesFact that is older than 36 months as quickly as possible.
Which three actions should you perform in sequence in a stored procedure? 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: Create an empty table named SalesFact_work that has the same schema as SalesFact.
Step 2: Switch the partition containing the stale data from SalesFact to SalesFact_Work.
SQL Data Warehouse supports partition splitting, merging, and switching. To switch partitions between two tables, you must ensure that the partitions align on their respective boundaries and that the table definitions match.
Loading data into partitions with partition switching is a convenient way stage new data in a table that is not visible to users the switch in the new data.
Step 3: Drop the SalesFact_Work table.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-partition

QUESTION NO: 5
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

CWNP CWISA-102 - もし不合格になったら、私たちは全額返金することを保証します。 Salesforce B2C-Commerce-Architect - NewValidDumpsを選ぶなら、絶対に後悔させません。 NewValidDumpsのMicrosoftのMicrosoft PL-400J試験トレーニング資料は試験問題と解答を含まれて、豊富な経験を持っているIT業種の専門家が長年の研究を通じて作成したものです。 私たちは最も新しくて、最も正確性の高いMicrosoftのMicrosoft SC-200試験トレーニング資料を提供します。 Splunk SPLK-1002 - 我々の誠意を信じてください。

Updated: May 28, 2022