Microsoft DP-203 Exam Dumps

Get All Data Engineering on Microsoft Azure Exam Questions with Validated Answers

DP-203 Pack
Vendor: Microsoft
Exam Code: DP-203
Exam Name: Data Engineering on Microsoft Azure
Exam Questions: 354
Last Updated: May 26, 2026
Related Certifications:
Exam Tags: Intermediate Microsoft Data Engineers
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Free Microsoft DP-203 Exam Actual Questions

Question No. 1

You have an Azure Synapse Analytics dedicated SQL pool named Pool1.

Pool! contains two tables named SalesFact_Stagmg and SalesFact. Both tables have a matching number of partitions, all of which contain data.

You need to load data from SalesFact_Staging to SalesFact by switching a partition.

What should you specify when running the alter TABLE statement?

Show Answer Hide Answer
Correct Answer: B

Question No. 2

You build a data warehouse in an Azure Synapse Analytics dedicated SQL pool.

Analysts write a complex SELECT query that contains multiple JOIN and CASE statements to transform data for use in inventory reports. The inventory reports will use the data and additional WHERE parameters depending on the report. The reports will be produced once daily.

You need to implement a solution to make the dataset available for the reports. The solution must minimize query times.

What should you implement?

Show Answer Hide Answer
Correct Answer: A

Materialized views for dedicated SQL pools in Azure Synapse provide a low maintenance method for complex analytical queries to get fast performance without any query change.

Note: When result set caching is enabled, dedicated SQL pool automatically caches query results in the user database for repetitive use. This allows subsequent query executions to get results directly from the persisted cache so recomputation is not needed. Result set caching improves query performance and reduces compute resource usage. In addition, queries using cached results set do not use any concurrency slots and thus do not count against existing concurrency limits.


https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/performance-tuning-materialized-views

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/performance-tuning-result-set-caching

Question No. 3

You are implementing a batch dataset in the Parquet format.

Data tiles will be produced by using Azure Data Factory and stored in Azure Data Lake Storage Gen2. The files will be consumed by an Azure Synapse Analytics serverless SQL pool.

You need to minimize storage costs for the solution.

What should you do?

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Correct Answer: C

An external table points to data located in Hadoop, Azure Storage blob, or Azure Data Lake Storage. External tables are used to read data from files or write data to files in Azure Storage. With Synapse SQL, you can use external tables to read external data using dedicated SQL pool or serverless SQL pool.


https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables

Question No. 4

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 scenario, 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 Storage account that contains 100 GB of files. The files contain text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.

You plan to copy the data from the storage account to an Azure SQL data warehouse.

You need to prepare the files to ensure that the data copies quickly.

Solution: You modify the files to ensure that each row is less than 1 MB.

Does this meet the goal?

Show Answer Hide Answer
Correct Answer: A

When exporting data into an ORC File Format, you might get Java out-of-memory errors when there are large text columns. To work around this limitation, export only a subset of the columns.


https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data

Question No. 5

You are designing an inventory updates table in an Azure Synapse Analytics dedicated SQL pool. The table will have a clustered columnstore index and will include the following columns:

You identify the following usage patterns:

Analysts will most commonly analyze transactions for a warehouse.

Queries will summarize by product category type, date, and/or inventory event type.

You need to recommend a partition strategy for the table to minimize query times.

On which column should you partition the table?

Show Answer Hide Answer
Correct Answer: C

The number of records for each warehouse is big enough for a good partitioning.

Note: Table partitions enable you to divide your data into smaller groups of data. In most cases, table partitions are created on a date column.

When creating partitions on clustered columnstore tables, it is important to consider how many rows belong to each partition. For optimal compression and performance of clustered columnstore tables, a minimum of 1 million rows per distribution and partition is needed. Before partitions are created, dedicated SQL pool already divides each table into 60 distributed databases.


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