100% PASS QUIZ 2025 MICROSOFT MARVELOUS DP-203: EXAM DATA ENGINEERING ON MICROSOFT AZURE QUIZZES

100% Pass Quiz 2025 Microsoft Marvelous DP-203: Exam Data Engineering on Microsoft Azure Quizzes

100% Pass Quiz 2025 Microsoft Marvelous DP-203: Exam Data Engineering on Microsoft Azure Quizzes

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In addition, you can print these Microsoft DP-203 PDF questions for paper study in this format of ExamsLabs product frees you from restrictions of time and place as you can study DP-203 exam questions from your comfort zone in your spare time. The second version is the web-based format of the Microsoft DP-203 Practice Test. Browsers such as Internet Explorer, Microsoft Edge, Firefox, Safari, and Chrome support the web-based practice exam.

The Microsoft DP-203 Exam measures a candidate's ability to develop solutions using Azure services like Azure Data Lake Storage, Azure Synapse Analytics, Azure Databricks, and Azure Stream Analytics. A candidate's knowledge on how to design and implement data processing solutions on Azure is also evaluated in the exam. Data Engineering on Microsoft Azure certification is ideal for data engineers who wish to demonstrate their ability to design and implement data solutions using Microsoft Azure services.

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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q240-Q245):

NEW QUESTION # 240
You have an enterprise data warehouse in Azure Synapse Analytics named DW1 on a server named Server1.
You need to verify whether the size of the transaction log file for each distribution of DW1 is smaller than
160 GB.
What should you do?

  • A. From Azure Monitor in the Azure portal, execute a query against the logs of DW1.
  • B. Execute a query against the logs of DW1 by using theGet-AzOperationalInsightSearchResult PowerShell cmdlet.
  • C. On DW1, execute a query against the sys.database_files dynamic management view.
  • D. On the master database, execute a query against the sys.dm_pdw_nodes_os_performance_counters dynamic management view.

Answer: D

Explanation:
The following query returns the transaction log size on each distribution. If one of the log files is reaching 160 GB, you should consider scaling up your instance or limiting your transaction size.
-- Transaction log size
SELECT
instance_name as distribution_db,
cntr_value*1.0/1048576 as log_file_size_used_GB,
pdw_node_id
FROM sys.dm_pdw_nodes_os_performance_counters
WHERE
instance_name like 'Distribution_%'
AND counter_name = 'Log File(s) Used Size (KB)'
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-monitor


NEW QUESTION # 241
You have an Azure data factory that has the Git repository settings shown in the following exhibit.

Use the drop-down menus to select the answer choose that completes each statement based on the information presented in the graphic.
NOTE: Each correct answer is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 242
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 section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
* A workload for data engineers who will use Python and SQL.
* A workload for jobs that will run notebooks that use Python, Scala, and SOL.
* A workload that data scientists will use to perform ad hoc analysis in Scala and R.
The enterprise architecture team at your company identifies the following standards for Databricks environments:
* The data engineers must share a cluster.
* The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
* All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databricks clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?

  • A. No
  • B. Yes

Answer: A

Explanation:
Explanation
We would need a High Concurrency cluster for the jobs.
Note:
Standard clusters are recommended for a single user. Standard can run workloads developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
Reference:
https://docs.azuredatabricks.net/clusters/configure.html


NEW QUESTION # 243
You have a data model that you plan to implement in a data warehouse in Azure Synapse Analytics as shown in the following exhibit.

All the dimension tables will be less than 2 GB after compression, and the fact table will be approximately 6 TB.
Which type of table should you use for each table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 244
You have an Azure Synapse Analytics dedicated SQL pool named Pool1. Pool1 contains a fact table named Tablet. Table1 contains sales data. Sixty-five million rows of data are added to Table1 monthly.
At the end of each month, you need to remove data that is older than 36 months. The solution must minimize how long it takes to remove the data.
How should you partition Table1, and how should you remove the old data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation


NEW QUESTION # 245
......

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