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Azure Data Engineer Associate DP-200 ここには、私たちは君の需要に応じます。

Azure Data Engineer Associate DP-200日本語復習赤本 - Implementing an Azure Data Solution 君の初めての合格を目標にします。 うちのMicrosoftのDP-200 関連資料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。君がうち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。

多くの人々は高い難度のIT認証試験に合格するのは専門の知識が必要だと思います。それは確かにそうですが、その知識を身につけることは難しくないとといわれています。IT業界ではさらに強くなるために強い専門知識が必要です。

Microsoft DP-200日本語復習赤本 - 我々の誠意を信じてください。

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DP-200 PDF DEMO:

QUESTION NO: 1
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: 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 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

QUESTION NO: 4
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You develop a data ingestion process that will import data to a Microsoft Azure SQL Data Warehouse.
The data to be ingested resides in parquet files stored in an Azure Data lake Gen 2 storage account.
You need to load the data from the Azure Data Lake Gen 2 storage account into the Azure SQL Data
Warehouse.
Solution:
1. Create an external data source pointing to the Azure storage account
2. Create a workload group using the Azure storage account name as the pool name
3. Load the data using the INSERT...SELECT statement
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation
You need to create an external file format and external table using the external data source.
You then load the data using the CREATE TABLE AS SELECT statement.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure- data-lake-store

QUESTION NO: 5
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

Palo Alto Networks PCNSE - それは確かに君の試験に役に立つとみられます。 Salesforce Media-Cloud-Consultant - 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。 Huawei H12-811-ENU - が、サイトに相関する依頼できる保証が何一つありません。 短時間でMicrosoft MB-310J試験に一発合格したいなら、我々社のMicrosoftのMicrosoft MB-310J資料を参考しましょう。 MicrosoftのMicrosoft DP-420J試験はNewValidDumpsの保証を検証することができ、１００パーセントの合格率に達することができます。

Updated: May 28, 2022