Microsoft DP-203 Practice Exam Questions

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Introducing DP-203 Microsoft Azure Data Engineer Certification Exam:

DP-203 is a Microsoft Certification Exam that tests candidates for their knowledge and skills in designing and implementing data solutions in Azure. It is for data engineers responsible for building analytics solutions.

There is hype for data engineers in the industry, making Microsoft Azure Data Engineer Certification a must-have. This certification is globally recognized and leads to job promotions and salary increases.

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Exam DP-203; Learning the Essentials of Microsoft Azure Data Engineer:

The DP-203 exam consists of 40-60 multiple-choice and multiple-answer questions. The exam is timed for 180 minutes. The exam is available in multiple languages, i.e., English, Japanese, Korean, and Simplified Chinese.

To register for the DP-203 exam, visit the Microsoft website. There, create an account and sign in to schedule your exam. The cost of the exam is $165.

The DP-203 exam consists of the following subject areas according to the given percentage:

●    Design and implement data storage (15–20%)
●    Develop data processing (40–45%)
●    Secure, monitor, and optimize data storage and data processing (30–35%)

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Related Exams

DP-203 Test 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?












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?






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
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,

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?








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.

You need to trigger an Azure Data Factory pipeline when a file arrives in an Azure Data Lake Storage Gen2 container.
Which resource provider should you enable?










Event-driven architecture (EDA) is a common data integration pattern that involves
production, detection, consumption, and reaction to events. Data integration scenarios
often require Data Factory customers to trigger pipelines based on events happening in
storage account, such as the arrival or deletion of a file in Azure Blob Storage account.
Data Factory natively integrates with Azure Event Grid, which lets you trigger pipelines on
such events.

You are designing a financial transactions table in an Azure Synapse Analytics dedicated SQL pool. The table will have a clustered columnstore index and will include the following columns:
TransactionType: 40 million rows per transaction type
CustomerSegment: 4 million per customer segment
TransactionMonth: 65 million rows per month
AccountType: 500 million per account type
You have the following query requirements:
Analysts will most commonly analyze transactions for a given month.
Transactions analysis will typically summarize transactions by transaction type,
customer segment, and/or account type
You need to recommend a partition strategy for the table to minimize query times.
On which column should you recommend partitioning the table?










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.
Example: Any partitioning added to a table is in addition to the distributions created behind
the scenes. Using this example, if the sales fact table contained 36 monthly partitions, and
given that a dedicated SQL pool has 60 distributions, then the sales fact table should
contain 60 million rows per month, or 2.1 billion rows when all months are populated. If a
table contains fewer than the recommended minimum number of rows per partition,
consider using fewer partitions in order to increase the number of rows per partition.

You have an Azure Stream Analytics job.
You need to ensure that the job has enough streaming units provisioned
You configure monitoring of the SU % Utilization metric.
Which two additional metrics should you monitor? Each correct answer presents part of the
NOTE Each correct selection is worth one point


Out of order Events


Late Input Events


Baddogged Input Events


Function Events

Baddogged Input Events

You plan to perform batch processing in Azure Databricks once daily.
Which type of Databricks cluster should you use?


High Concurrency






Azure Databricks has two types of clusters: interactive and automated. You use interactive
clusters to analyze data collaboratively with interactive notebooks. You use automated
clusters to run fast and robust automated jobs.
Example: Scheduled batch workloads (data engineers running ETL jobs)
This scenario involves running batch job JARs and notebooks on a regular cadence
through the Databricks platform.
The suggested best practice is to launch a new cluster for each run of critical jobs. This
helps avoid any issues (failures, missing SLA, and so on) due to an existing workload
(noisy neighbor) on a shared cluster.

You configure version control for an Azure Data Factory instance as shown in the following exhibit.

You have an Azure Synapse Analytics dedicated SQL pool named Pool1 and a database named DB1. DB1 contains a fact table named Table1.
You need to identify the extent of the data skew in Table1.
What should you do in Synapse Studio?


Connect to the built-in pool and query sysdm_pdw_sys_info.


Connect to Pool1 and run DBCC CHECKALLOC.


Connect to the built-in pool and run DBCC CHECKALLOC.


Connect to Pool! and query sys.dm_pdw_nodes_db_partition_stats.

Connect to Pool! and query sys.dm_pdw_nodes_db_partition_stats.

Microsoft recommends use of sys.dm_pdw_nodes_db_partition_stats to analyze any
skewness in the data.

You are creating a new notebook in Azure Databricks that will support R as the primary language but will also support Scale and SOL Which switch should you use to switch between languages?










To change the language in Databricks’ cells to either Scala, SQL, Python or R, prefix the
cell with ‘%’, followed by the language.
%python //or r, scala, sql

You store files in an Azure Data Lake Storage Gen2 container. The container has the storage policy shown in the following exhibit

You are building an Azure Synapse Analytics dedicated SQL pool that will contain a fact
table for transactions from the first half of the year 2020.
You need to ensure that the table meets the following requirements:
Minimizes the processing time to delete data that is older than 10 years
Minimizes the I/O for queries that use year-to-date values
How should you complete the Transact-SQL statement? To answer, select the appropriate
options in the answer area.
NOTE: Each correct selection is worth one point.

You manage an enterprise data warehouse in Azure Synapse Analytics.
Users report slow performance when they run commonly used queries. Users do not report
performance changes for infrequently used queries.
You need to monitor resource utilization to determine the source of the performance
issues. Which metric should you monitor?


Data IO percentage


Local tempdb percentage


Cache used percentage


DWU percentage

Cache used percentage

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Real Exam Scenario Simulation:

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