TRY 2PASS4SURE UPDATED MICROSOFT DP-203 QUESTIONS FOR EASY AND QUICK PREPARATION

Try 2Pass4sure Updated Microsoft DP-203 Questions For Easy and Quick Preparation

Try 2Pass4sure Updated Microsoft DP-203 Questions For Easy and Quick Preparation

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Microsoft DP-203 (Data Engineering on Microsoft Azure) exam is a certification that validates an individual's knowledge and skills in designing and implementing data solutions using Microsoft Azure. Data Engineering on Microsoft Azure certification is designed for data engineers who are responsible for designing and implementing data solutions using various Azure services, including Azure Data Factory, Azure Databricks, Azure Stream Analytics, and Azure HDInsight. DP-203 Exam measures an individual's ability to design, implement, monitor and optimize data solutions using these services and ensures that the individual has the necessary skills to meet the growing demand for data engineers in the industry.

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The field of information technology has seen multiple advancements lately. Reputed companies around the globe have set the Data Engineering on Microsoft Azure DP-203 certification as criteria for multiple well-paid job roles. Only DP-203 certified will easily get high-paying posts in popular companies. Additionally, a Microsoft DP-203 Certification holder can climb the career ladder and get promotions within the current organization.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q140-Q145):

NEW QUESTION # 140
You have an Azure subscription that contains an Azure Synapse Analytics dedicated SQL pool named Pool1.
You use Azure Monitor.
You need to monitor the performance of queries executed in Pool1.
Which log should you query?

  • A. SynapseSqlPoolSqlRequests
  • B. SynapseSqlPoolWaits
  • C. SynapseSqlPoolRequestSteps
  • D. SynapseSqlPoolExecRequests

Answer: D

Explanation:
* SynapseSqlPoolExecRequests:
* This log contains detailed information about queries executed in a dedicated SQL pool in Azure Synapse Analytics.
* It provides metrics such as query duration, CPU time, I/O, and the status of the queries, making it the best choice for monitoring query performance.
* Other options:
* A. SynapseSqlPoolSqlRequests:
* Logs high-level requests, such as login attempts or connection establishment. It doesn't give detailed query execution information.
* C. SynapseSqlPoolWaits:
* Contains information about waits in the SQL pool, useful for troubleshooting resource contention but not suitable for directly monitoring query performance.
* D. SynapseSqlPoolRequestSteps:
* Provides information about the individual steps within a query plan, which is more granular and not typically used for general query performance monitoring.


NEW QUESTION # 141
You have an Azure Data Lake Storage account that contains CSV files. The CSV files contain sales order data and are partitioned by using the following format.
/data/salesorders/year=xxxx/month-y
You need to retrieve only the sales orders from January 2023 and February 2023.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 142
You have an Azure subscription that contains an Azure Synapse Analytics workspace named workspace1.
Workspace1 contains a dedicated SQL pool named SQL Pool and an Apache Spark pool named sparkpool.
Sparkpool1 contains a DataFrame named pyspark.df.
You need to write the contents of pyspark_df to a tabte in SQLPooM by using a PySpark notebook.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 143
You need to build a solution to ensure that users can query specific files in an Azure Data Lake Storage Gen2 account from an Azure Synapse Analytics serverless SQL pool.
Which three 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.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Answer:

Explanation:

Explanation:

Step 1: Create an external data source
You can create external tables in Synapse SQL pools via the following steps:
CREATE EXTERNAL DATA SOURCE to reference an external Azure storage and specify the credential that should be used to access the storage.
CREATE EXTERNAL FILE FORMAT to describe format of CSV or Parquet files.
CREATE EXTERNAL TABLE on top of the files placed on the data source with the same file format.
Step 2: Create an external file format object
Creating an external file format is a prerequisite for creating an external table.
Step 3: Create an external table
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables


NEW QUESTION # 144
You have an Azure data factory.
You need to ensure that pipeline-run data is retained for 120 days. The solution must ensure that you can query the data by using the Kusto query language.
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.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Answer:

Explanation:

Explanation:

Step 1: Create an Azure Storage account that has a lifecycle policy
To automate common data management tasks, Microsoft created a solution based on Azure Data Factory. The service, Data Lifecycle Management, makes frequently accessed data available and archives or purges other data according to retention policies. Teams across the company use the service to reduce storage costs, improve app performance, and comply with data retention policies.
Step 2: Create a Log Analytics workspace that has Data Retention set to 120 days.
Data Factory stores pipeline-run data for only 45 days. Use Azure Monitor if you want to keep that data for a longer time. With Monitor, you can route diagnostic logs for analysis to multiple different targets, such as a Storage Account: Save your diagnostic logs to a storage account for auditing or manual inspection. You can use the diagnostic settings to specify the retention time in days.
Step 3: From Azure Portal, add a diagnostic setting.
Step 4: Send the data to a log Analytics workspace,
Event Hub: A pipeline that transfers events from services to Azure Data Explorer.
Keeping Azure Data Factory metrics and pipeline-run data.
Configure diagnostic settings and workspace.
Create or add diagnostic settings for your data factory.
* In the portal, go to Monitor. Select Settings > Diagnostic settings.
* Select the data factory for which you want to set a diagnostic setting.
* If no settings exist on the selected data factory, you're prompted to create a setting. Select Turn on diagnostics.
* Give your setting a name, select Send to Log Analytics, and then select a workspace from Log Analytics Workspace.
* Select Save.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/monitor-using-azure-monitor


NEW QUESTION # 145
......

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