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Azure Data Engineer Associate DP-200 そうだったら、下記のものを読んでください。

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Microsoft DP-200試験解答 - 何の問題があったらお気軽に聞いてください。

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DP-200 PDF DEMO:

QUESTION NO: 1
You are responsible for providing access to an Azure Data Lake Storage Gen2 account.
Your user account has contributor access to the storage account, and you have the application ID access key.
You plan to use PolyBase to load data into Azure SQL data warehouse.
You need to configure PolyBase to connect the data warehouse to the storage account.
Which three components should you create in sequence? To answer, move the appropriate components from the list of components to the answer are and arrange them in the correct order.
Answer:
Explanation
Step 1: a database scoped credential
To access your Data Lake Storage account, you will need to create a Database Master Key to encrypt your credential secret used in the next step. You then create a database scoped credential.
Step 2: an external data source
Create the external data source. Use the CREATE EXTERNAL DATA SOURCE command to store the location of the data. Provide the credential created in the previous step.
Step 3: an external file format
Configure data format: To import the data from Data Lake Storage, you need to specify the External
File Format. This object defines how the files are written in Data Lake Storage.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-from-azure- data-lake-store

QUESTION NO: 2
You need to replace the SSIS process by using Data Factory.
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
Scenario: A daily process creates reporting data in REPORTINGDB from the data in SALESDB. The process is implemented as a SQL Server Integration Services (SSIS) package that runs a stored procedure from SALESDB.
Step 1: Create a linked service to each database
Step 2: Create two datasets
You can create two datasets: InputDataset and OutputDataset. These datasets are of type AzureBlob.
They refer to the Azure Storage linked service that you created in the previous section.
Step 3: Create a pipeline
You create and validate a pipeline with a copy activity that uses the input and output datasets.
Step 4: Add a copy activity
References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal

QUESTION NO: 3
You plan to deploy an Azure Cosmos DB database that supports multi-master replication.
You need to select a consistency level for the database to meet the following requirements:
* Provide a recovery point objective (RPO) of less than 15 minutes.
* Provide a recovery time objective (RTO) of zero minutes.
What are three possible consistency levels that you can select? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Consistent Prefix
B. Session
C. Bounded Staleness
D. Strong
E. Eventual
Answer: A,B,E
Explanation
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels-choosing

QUESTION NO: 4
You are monitoring an Azure Stream Analytics job.
You discover that the Backlogged Input Events metric is increasing slowly and is consistently non- zero.
You need to ensure that the job can handle all the events.
What should you do?
A. Change the compatibility level of the Stream Analytics job.
B. Create an additional output stream for the existing input stream.
C. Remove any named consumer groups from the connection and use $default.
D. Increase the number of streaming units (SUs).
Answer: D
Explanation
Backlogged Input Events: Number of input events that are backlogged. A non-zero value for this metric implies that your job isn't able to keep up with the number of incoming events. If this value is slowly increasing or consistently non-zero, you should scale out your job. You should increase the
Streaming Units.
Note: Streaming Units (SUs) represents the computing resources that are allocated to execute a
Stream Analytics job. The higher the number of SUs, the more CPU and memory resources are allocated for your job.
Reference:
https://docs.microsoft.com/bs-cyrl-ba/azure/stream-analytics/stream-analytics-monitoring

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 are developing a solution that will use Azure Stream Analytics. The solution will accept an Azure
Blob storage file named Customers. The file will contain both in-store and online customer details.
The online customers will provide a mailing address.
You have a file in Blob storage named LocationIncomes that contains based on location. The file rarely changes.
You need to use an address to look up a median income based on location. You must output the data to Azure SQL Database for immediate use and to Azure Data Lake Storage Gen2 for long-term retention.
Solution: You implement a Stream Analytics job that has one streaming input, one reference input, two queries, and four outputs.
Does this meet the goal?
A. Yes
B. No
Answer: A
Explanation
We need one reference data input for LocationIncomes, which rarely changes.
We need two queries, on for in-store customers, and one for online customers.
For each query two outputs is needed.
Note: Stream Analytics also supports input known as reference data. Reference data is either completely static or changes slowly.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-add-inputs#stream-and- reference-input
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs

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Updated: May 28, 2022