Microsoft crack4sure dp-203 Actual Questions by Olivier q55 vce pdf

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Exam Name:	Data Engineering on Microsoft Azure
Exam Code:	DP-203 Dumps
Vendor:	Microsoft	Certification:	Microsoft Certified: Azure Data Engineer Associate
Questions:	361 Q&A's	Shared By:	olivier

Question 24

You have an Azure Data Lake Storage Gen2 account named adls2 that is protected by a virtual network.

You are designing a SQL pool in Azure Synapse that will use adls2 as a source.

What should you use to authenticate to adls2?

Options:

a shared access signature (SAS)

a managed identity

a shared key

an Azure Active Directory (Azure AD) user

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Question 25

You have an Azure Synapse Analytics dedicated SQL pool named Pool1 that contains a table named Sales. Sales has row-level security (RLS) applied. RLS uses the following predicate filter.

Questions 25

A user named SalesUser1 is assigned the db_datareader role for Pool1. Which rows in the Sales table are returned when SalesUser1 queries the table?

Options:

only the rows for which the value in the User_Name column is SalesUser1

all the rows

only the rows for which the value in the SalesRep column is Manager

only the rows for which the value in the SalesRep column is SalesUser1

Discussion

Question 26

You have an Azure Data Factory pipeline that performs an incremental load of source data to an Azure Data Lake Storage Gen2 account.

Data to be loaded is identified by a column named LastUpdatedDate in the source table.

You plan to execute the pipeline every four hours.

You need to ensure that the pipeline execution meets the following requirements:

Automatically retries the execution when the pipeline run fails due to concurrency or throttling limits.

Supports backfilling existing data in the table.

Which type of trigger should you use?

Options:

Storage event

on-demand

schedule

tumbling window

Discussion

Question 27

You have an Azure Data Lake Storage account that contains a staging zone.

You need to design a dairy process to ingest incremental data from the staging zone, transform the data by executing an R script, and then insert the transformed data into a data warehouse in Azure Synapse Analytics.

Solution: You use an Azure Data Factory schedule trigger to execute a pipeline that copies the data to a staging table in the data warehouse, and then uses a stored procedure to execute the R script.

Does this meet the goal?

Options:

Yes