Microsoft DP-203 Exam Dumps


Vendor Name: Microsoft
Certification Name: Microsoft Azure Data Engineer Associate
Exam Name: Data Engineering on Microsoft Azure

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Microsoft DP-203 Exam Questions


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Data Engineering on Microsoft Azure Exams
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DP-203 Exam Sample Questions:



You are designing the folder structure for an Azure Data Lake Storage Gen2 account.
You identify the following usage patterns:
• Users will query data by using Azure Synapse Analytics serverless SQL pools and Azure
Synapse Analytics serverless Apache Spark pods.
• Most queries will include a filter on the current year or week.
• Data will be secured by data source.
You need to recommend a folder structure that meets the following requirements:
• Supports the usage patterns
• Simplifies folder security
• Minimizes query times
Which folder structure should you recommend?

 

Option A

 

Option B

 

Option C

 

Option D

 

Option E


Option D






You have an Azure Databricks resource.
You need to log actions that relate to changes in compute for the Databricks resource.
Which Databricks services should you log?

 

clusters

 

workspace

 

DBFS

 

SSH

 

lobs


workspace






You have an Azure Data lake Storage account that contains a staging zone.
You need to design a daily 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
executes an Azure Databricks notebook, and then inserts the data into the data warehouse
Dow this meet the goal?

 

Yes

 

No


Yes






You need to implement a Type 3 slowly changing dimension (SCD) for product category
data in an Azure Synapse Analytics dedicated SQL pool.
You have a table that was created by using the following Transact-SQL statement.

Which two columns should you add to the table? Each correct answer presents part of the
solution.
NOTE: Each correct selection is worth one point.

 

[EffectiveScarcDate] [datetime] NOT NULL,

 

[CurrentProduccCacegory] [nvarchar] (100) NOT NULL,

 

[EffectiveEndDace] [dacecime] NULL,

 

[ProductCategory] [nvarchar] (100) NOT NULL,

 

[OriginalProduccCacegory] [nvarchar] (100) NOT NULL,


[CurrentProduccCacegory] [nvarchar] (100) NOT NULL,


[OriginalProduccCacegory] [nvarchar] (100) NOT NULL,


Explanation:
A Type 3 SCD supports storing two versions of a dimension member as separate columns.
The table includes a column for the current value of a member plus either the original or
previous value of the member. So Type 3 uses additional columns to track one key
instance of history, rather than storing additional rows to track each change like in a Type 2 





You plan to build a structured streaming solution in Azure Databricks. The solution will count new events in five-minute intervals and report only events that arrive during the interval. The output will be sent to a Delta Lake table.
Which output mode should you use?

 

complete

 

update

 

append


append


Explanation: Append Mode: Only new rows appended in the result table since the last
trigger are written to external storage. This is applicable only for the queries where existing
rows in the Result Table are not expected to change.
https://docs.databricks.com/getting-started/spark/streaming.html



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