Dumps DP-203 Cost, Valid DP-203 Test Practice

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Microsoft DP-203 exam covers a wide range of topics that are essential for data engineers working on the Azure platform. DP-203 exam focuses on topics such as designing and implementing data storage solutions using Azure Blob Storage, Azure Cosmos DB, and Azure SQL Database. DP-203 Exam also covers topics such as data processing using Azure Data Factory, Azure Databricks, and Azure Stream Analytics. Additionally, the exam tests the candidate's knowledge of Azure Data Lake Storage and Azure Synapse Analytics for implementing big data solutions.

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Microsoft DP-203 (Data Engineering on Microsoft Azure) certification is a highly sought-after accreditation for data engineers who want to demonstrate their knowledge and skills in designing and implementing data solutions on the Azure platform. Data Engineering on Microsoft Azure certification validates a candidate's technical expertise in building data processing systems, data storage solutions, and data transformation and integration solutions using Azure services.

Data Engineering on Microsoft Azure Exam Certification Details:

Passing Score	700 / 1000
Books / Training	DP-203T00: Data Engineering on Microsoft Azure
Duration	150 mins
Exam Name	Microsoft Certified - Azure Data Engineer Associate
Sample Questions	Data Engineering on Microsoft Azure Sample Questions

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q51-Q56):

NEW QUESTION # 51
You plan to create a real-time monitoring app that alerts users when a device travels more than 200 meters away from a designated location.
You need to design an Azure Stream Analytics job to process the data for the planned app. The solution must minimize the amount of code developed and the number of technologies used.
What should you include in the Stream Analytics job? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Input type: Stream
You can process real-time IoT data streams with Azure Stream Analytics.
Function: Geospatial
With built-in geospatial functions, you can use Azure Stream Analytics to build applications for scenarios such as fleet management, ride sharing, connected cars, and asset tracking.
Note: In a real-world scenario, you could have hundreds of these sensors generating events as a stream.
Ideally, a gateway device would run code to push these events to Azure Event Hubs or Azure IoT Hubs.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-get-started-with-azure-stream- analytics-to-process-data-from-iot-devices
https://docs.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios

NEW QUESTION # 52
You are designing a real-time dashboard solution that will visualize streaming data from remote sensors that connect to the internet. The streaming data must be aggregated to show the average value of each 10-second interval. The data will be discarded after being displayed in the dashboard.
The solution will use Azure Stream Analytics and must meet the following requirements:
Minimize latency from an Azure Event hub to the dashboard.
Minimize the required storage.
Minimize development effort.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-power-bi-dashboard

NEW QUESTION # 53
You have the following table named Employees.

You need to calculate the employee_type value based on the hire_date value.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation
Graphical user interface, text, application Description automatically generated

Box 1: CASE
CASE evaluates a list of conditions and returns one of multiple possible result expressions.
CASE can be used in any statement or clause that allows a valid expression. For example, you can use CASE in statements such as SELECT, UPDATE, DELETE and SET, and in clauses such as select_list, IN, WHERE, ORDER BY, and HAVING.
Syntax: Simple CASE expression:
CASE input_expression
WHEN when_expression THEN result_expression [ ...n ]
[ ELSE else_result_expression ]
END
Box 2: ELSE
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/case-transact-sql

NEW QUESTION # 54
You have the following Azure Stream Analytics query.

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:

Explanation:

Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/

NEW QUESTION # 55
You have an Azure subscription that contains an Azure Data Lake Storage account. The storage account contains a data lake named DataLake1.
You plan to use an Azure data factory to ingest data from a folder in DataLake1, transform the data, and land the data in another folder.
You need to ensure that the data factory can read and write data from any folder in the DataLake1 file system.
The solution must meet the following requirements:
Minimize the risk of unauthorized user access.
Use the principle of least privilege.
Minimize maintenance effort.
How should you configure access to the storage account for the data factory? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Box 1: Azure Active Directory (Azure AD)
On Azure, managed identities eliminate the need for developers having to manage credentials by providing an identity for the Azure resource in Azure AD and using it to obtain Azure Active Directory (Azure AD) tokens.
Box 2: a managed identity
A data factory can be associated with a managed identity for Azure resources, which represents this specific data factory. You can directly use this managed identity for Data Lake Storage Gen2 authentication, similar to using your own service principal. It allows this designated factory to access and copy data to or from your Data Lake Storage Gen2.
Note: The Azure Data Lake Storage Gen2 connector supports the following authentication types.
Account key authentication
Service principal authentication
Managed identities for Azure resources authentication
Reference:
https://docs.microsoft.com/en-us/azure/active-directory/managed-identities-azure-resources/overview
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-data-lake-storage

NEW QUESTION # 56
......

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DUMPS DP-203 COST, VALID DP-203 TEST PRACTICE

Dumps DP-203 Cost, Valid DP-203 Test Practice