MICROSOFT DP-203 DATA ENGINEERING ON MICROSOFT AZURE QUESTIONS - WITH 25% DISCOUNT OFFER [2025]

Microsoft DP-203 Data Engineering on Microsoft Azure Questions - With 25% Discount Offer [2025]

Microsoft DP-203 Data Engineering on Microsoft Azure Questions - With 25% Discount Offer [2025]

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Microsoft DP-203 (Data Engineering on Microsoft Azure) Exam is a certification exam that tests the skills and knowledge of candidates in designing and implementing data solutions on Microsoft Azure. DP-203 exam is designed for data engineers who work with data storage, processing, and analysis on Azure. DP-203 exam covers a range of topics such as data ingestion, transformation, storage, and processing using Azure services like Azure Data Factory, Azure Databricks, Azure Stream Analytics, and more.

The DP-203 Exam focuses on various topics, including data storage solutions, data processing solutions, data monitoring and optimization, and implementing security and privacy measures in data solutions. Candidates who pass DP-203 exam will prove their proficiency in designing and implementing data solutions, integrating data solutions with other services and tools, and implementing data security and privacy measures.

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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q305-Q310):

NEW QUESTION # 305
In Azure Data Factory, you have a schedule trigger that is scheduled in Pacific Time.
Pacific Time observes daylight saving time.
The trigger has the following JSON file.

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

Answer:

Explanation:


NEW QUESTION # 306
You have an Azure Databricks workspace that contains a Delta Lake dimension table named Tablet. Table1 is a Type 2 slowly changing dimension (SCD) table. You need to apply updates from a source table to Table1.
Which Apache Spark SQL operation should you use?

  • A. CREATE
  • B. UPDATE
  • C. ALTER
  • D. MERGE

Answer: D

Explanation:
The Delta provides the ability to infer the schema for data input which further reduces the effort required in managing the schema changes. The Slowly Changing Data(SCD) Type 2 records all the changes made to each key in the dimensional table. These operations require updating the existing rows to mark the previous values of the keys as old and then inserting new rows as the latest values. Also, Given a source table with the updates and the target table with dimensional data, SCD Type 2 can be expressed with the merge.
Example:
// Implementing SCD Type 2 operation using merge function
customersTable
as("customers")
merge(
stagedUpdates.as("staged_updates"),
"customers.customerId = mergeKey")
whenMatched("customers.current = true AND customers.address <> staged_updates.address") updateExpr(Map(
"current" -> "false",
"endDate" -> "staged_updates.effectiveDate"))
whenNotMatched()
insertExpr(Map(
"customerid" -> "staged_updates.customerId",
"address" -> "staged_updates.address",
"current" -> "true",
"effectiveDate" -> "staged_updates.effectiveDate",
"endDate" -> "null"))
execute()
}
Reference:
https://www.projectpro.io/recipes/what-is-slowly-changing-data-scd-type-2-operation-delta-table-databricks


NEW QUESTION # 307
You have a SQL pool in Azure Synapse.
A user reports that queries against the pool take longer than expected to complete.
You need to add monitoring to the underlying storage to help diagnose the issue.
Which two metrics should you monitor? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. Snapshot Storage Size
  • B. Cache used percentage
  • C. Active queries
  • D. Cache hit percentage
  • E. DWU Limit

Answer: B,D

Explanation:
A: Cache used is the sum of all bytes in the local SSD cache across all nodes and cache capacity is the sum of the storage capacity of the local SSD cache across all nodes.
E: Cache hits is the sum of all columnstore segments hits in the local SSD cache and cache miss is the columnstore segments misses in the local SSD cache summed across all nodes Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-concept-resour


NEW QUESTION # 308
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 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 schedule an Azure Databricks job that executes an R notebook, and then inserts the data into the data warehouse.
Does this meet the goal?

  • A. No
  • B. Yes

Answer: A

Explanation:
Explanation
Must use an Azure Data Factory, not an Azure Databricks job.
Reference:
https://docs.microsoft.com/en-US/azure/data-factory/transform-data


NEW QUESTION # 309
You have a table in an Azure Synapse Analytics dedicated SQL pool. The table was created by using the following Transact-SQL statement.

You need to alter the table to meet the following requirements:
* Ensure that users can identify the current manager of employees.
* Support creating an employee reporting hierarchy for your entire company.
* Provide fast lookup of the managers' attributes such as name and job title.
Which column should you add to the table?

  • A. [ManagerEmployeeID] [int] NULL
  • B. [ManagerEmployeeKey] [int] NULL
  • C. [ManagerEmployeeID] [smallint] NULL
  • D. [ManagerName] [varchar](200) NULL

Answer: A

Explanation:
Use the same definition as the EmployeeID column.
Reference:
https://docs.microsoft.com/en-us/analysis-services/tabular-models/hierarchies-ssas-tabular


NEW QUESTION # 310
......

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