IT業の多くの人がいくつか認証試験にパスしたくて、それなりの合格証明書が君に最大な上昇空間を与えます。この競争の激しい業界でとんとん拍子に出世させるのはMicrosoftのDP-200勉強資料認定試験ですが、簡単にパスではありません。でもたくさんの方法があって、最も少ない時間をエネルギーをかかるのは最高です。 ところで、受験生の皆さんを簡単にIT認定試験に合格させられる方法がないですか。もちろんありますよ。 そのデザインは当面の急速に変化するIT市場と密接な関係があります。

Azure Data Engineer Associate DP-200 でないと、絶対後悔しますよ。

我々のMicrosoftのDP-200 - Implementing an Azure Data Solution勉強資料ソフトを利用してお客様の高通過率及び我々の技術の高いチームで、我々は自信を持って我々NewValidDumpsは専門的なのだと言えます。 MicrosoftのDP-200 専門知識の認定試験の認可を取ったら、あなたは望むキャリアを得ることができるようになります。NewValidDumpsのMicrosoftのDP-200 専門知識試験トレーニング資料を利用したら、望むことを取得できます。

あなたは各バーションのMicrosoftのDP-200勉強資料試験の資料をダウンロードしてみることができ、あなたに一番ふさわしいバーションを見つけることができます。暇な時間だけでMicrosoftのDP-200勉強資料試験に合格したいのですか。我々の提供するPDF版のMicrosoftのDP-200勉強資料試験の資料はあなたにいつでもどこでも読めさせます。

Microsoft DP-200勉強資料 - しかし、資料の品質が保証されることができません。

MicrosoftのDP-200勉強資料試験に合格することは容易なことではなくて、良い訓練ツールは成功の保証でNewValidDumpsは君の試験の問題を準備してしまいました。君の初めての合格を目標にします。

もし学習教材は問題があれば、或いは試験に不合格になる場合は、全額返金することを保証いたします。NewValidDumpsのMicrosoftのDP-200勉強資料試験トレーニング資料は正確性が高くて、カバー率も広い。

DP-200 PDF DEMO:

QUESTION NO: 1
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: 2
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: 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 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 need to mask tier 1 data. Which functions should you use? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation
A: Default
Full masking according to the data types of the designated fields.
For string data types, use XXXX or fewer Xs if the size of the field is less than 4 characters (char, nchar, varchar, nvarchar, text, ntext).
B: email
C: Custom text
Custom StringMasking method which exposes the first and last letters and adds a custom padding string in the middle. prefix,[padding],suffix Tier 1 Database must implement data masking using the following masking logic:
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking

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Updated: May 28, 2022