Microsoft DP-203 Dumps - Data Engineering on Microsoft Azure PDF Sample Questions

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Exam Code:
DP-203
Exam Name:
Data Engineering on Microsoft Azure
331 Questions
Last Update Date : 21 May, 2024
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DP-203 Complete Exam Detail

Detail Description
Total Time 180 minutes (3 hours)
Exam Fee $165 USD
Passing Marks 700 out of 1000
Available Languages English, Japanese
Exam Format Multiple choice, multiple answer, case studies, review screen, drag and drop, hot area, build list, short answer, mark review, review screen, and active screen types of questions
Exam Registration Through Microsoft's official exam registration portal or authorized exam provider
Prerequisites Intermediate knowledge of data engineering concepts and experience with implementing data solutions
Exam Skills Measured - Implement data storage solutions
- Implement data processing solutions
- Monitor and optimize data solutions
- Design and implement data security
- Design and implement data retention
Recommended Preparation - Hands-on experience with Azure data services
- Familiarity with Azure Portal, Azure PowerShell, Azure CLI, and Azure Resource Manager templates
- Understanding of Core Azure services, security, governance, privacy, and compliance features, and capabilities
Additional Resources - Official Microsoft DP-203 exam page
- Microsoft Learn DP-203 exam preparation path
- Third-party study materials and practice tests
Retake Policy If a candidate does not achieve a passing score on an exam the first time, the candidate must wait at least 24 hours before retaking the exam. If a candidate does not achieve a passing score the second time, the candidate must wait at least 14 days before retaking the exam a third time. A 14-day waiting period will be imposed for all subsequent exam retakes. There is no annual limit on the number of attempts on the same exam.

DP-203 Complete Exam Topics Breakdown

Exam Topic Description
Implement Data Storage Solutions - Implement Azure SQL data storage
- Implement Azure Data Lake Storage
- Implement Azure Blob Storage
- Implement Azure Cosmos DB storage
Implement Data Processing Solutions - Implement batch processing solutions
- Implement streaming solutions
- Implement data engineering pipelines
- Implement Azure Databricks
Monitor and Optimize Data Solutions - Monitor data storage
- Monitor data processing
- Optimize Azure Data solutions
Design and Implement Data Security - Implement authentication and authorization
- Implement data security and compliance
- Implement Azure Key Vault
Design and Implement Data Retention - Implement data retention policies
- Implement data archival
- Implement data lifecycle management

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Realexamdumps Providing most updated Azure Data Engineer Associate Question Answers. Here are a few exams:


Sample Questions

Realexamdumps Providing most updated Azure Data Engineer Associate Question Answers. Here are a few sample questions:

Microsoft DP-203 Sample Question 1

You are designing database for an Azure Synapse Analytics dedicated SQL pool to support workloads for detecting ecommerce transaction fraud.

Data will be combined from multiple ecommerce sites and can include sensitive financial information such as credit card numbers.

You need to recommend a solution that meets the following requirements:

  • Users must be able to identify potentially fraudulent transactions.
  • Users must be able to use credit cards as a potential feature in models.
  • Users must NOT be able to access the actual credit card numbers.

What should you include in the recommendation?


Options:

A. Transparent Data Encryption (TDE)
B. row-level security (RLS)
C. column-level encryption
D. Azure Active Directory (Azure AD) pass-through authentication

Answer: C Explanation: Explanation: Use Always Encrypted to secure the required columns. You can configure Always Encrypted for individual database columns containing your sensitive data. Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national identification numbers (for example, U.S. social security numbers), stored in Azure SQL Database or SQL Server databases.Reference: [Reference:, https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/always-encrypted-database-engine, , , ]

Microsoft DP-203 Sample Question 2

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 enterprise data warehouse in Azure Synapse Analytics.

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

Solution: You convert the files to compressed delimited text files.

Does this meet the goal?


Options:

A. Yes
B. No

Answer: A Explanation: Explanation: All file formats have different performance characteristics. For the fastest load, use compressed delimited text files.Reference: [Reference:, https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data, , , ]

Microsoft DP-203 Sample Question 3

You are designing a star schema for a dataset that contains records of online orders. Each record includes an order date, an order due date, and an order ship date.

You need to ensure that the design provides the fastest query times of the records when querying for arbitrary date ranges and aggregating by fiscal calendar attributes.

Which two actions should you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.


Options:

A. Create a date dimension table that has a DateTime key.
B. Use built-in SQL functions to extract date attributes.
C. Create a date dimension table that has an integer key in the format of yyyymmdd.
D. In the fact table, use integer columns for the date fields.
E. Use DateTime columns for the date fields.

Answer: B, E

Microsoft DP-203 Sample Question 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 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?


Options:

A. Yes
B. No

Answer: B 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 thatthey provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum querylatencies.Reference: [Reference:, https://docs.azuredatabricks.net/clusters/configure.html, , , ]

Microsoft DP-203 Sample Question 5

You need to design a solution that will process streaming data from an Azure Event Hub and output the data to Azure Data Lake Storage. The solution must ensure that analysts can interactively query the streaming data.

What should you use?


Options:

A. event triggers in Azure Data Factory
B. Azure Stream Analytics and Azure Synapse notebooks
C. Structured Streaming in Azure Databricks
D. Azure Queue storage and read-access geo-redundant storage (RA-GRS)

Answer: C

Microsoft DP-203 Sample Question 6

You need to design a data retention solution for the Twitter teed data records. The solution must meet the customer sentiment analytics requirements.

Which Azure Storage functionality should you include in the solution?


Options:

A. time-based retention
B. change feed
C. soft delete
D. Iifecycle management

Answer: E

Microsoft DP-203 Sample Question 7

You need to design a data retention solution for the Twitter feed data records. The solution must meet the customer sentiment analytics requirements.

Which Azure Storage functionality should you include in the solution?


Options:

A. change feed
B. soft delete
C. time-based retention
D. lifecycle management

Answer: B Explanation: Explanation: Scenario: Purge Twitter feed data records that are older than two years.Data sets have unique lifecycles. Early in the lifecycle, people access some data often. But the need for access often drops drastically as the data ages. Some data remains idle in the cloud and is rarely accessed once stored. Some data sets expire days or months after creation, while other data sets are actively read and modified throughout their lifetimes. Azure Storage lifecycle management offers a rule-based policy that you can use to transition blob data to the appropriate access tiers or to expire data at the end of the data lifecycle.Reference: [Reference:, https://docs.microsoft.com/en-us/azure/storage/blobs/lifecycle-management-overview, , , ]

Microsoft DP-203 Sample Question 8

You need to implement the surrogate key for the retail store table. The solution must meet the sales transaction

dataset requirements.

What should you create?


Options:

A. a table that has an IDENTITY property
B. a system-versioned temporal table
C. a user-defined SEQUENCE object
D. a table that has a FOREIGN KEY constraint

Answer: A Explanation: Explanation: Scenario: Implement a surrogate key to account for changes to the retail store addresses.A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the table data. Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the IDENTITY property to achieve this goal simply and effectively without affecting load performance.Reference: [Reference:, https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-identity, ]


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