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Microsoft DP-203 exam is designed for data engineers who want to demonstrate their expertise in designing and implementing data solutions on Microsoft Azure. DP-203 exam focuses on the deployment of various data platform technologies such as Azure Stream Analytics, Azure Data Factory, Azure Cosmos DB, and Azure SQL Database. The DP-203 Exam is an associate-level certification that validates a candidate's skills and knowledge required to design, implement and maintain data solutions on Azure.

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Microsoft DP-203 (Data Engineering on Microsoft Azure) Certification Exam is an excellent way to validate your skills and expertise in Azure data engineering. Passing the exam demonstrates your ability to design and implement data solutions using Azure services and can help you advance your career as a data engineer. If you are interested in pursuing this certification, it is recommended that you have experience with Azure services and are comfortable designing and implementing data solutions on the Azure platform.

Microsoft DP-203 (Data Engineering on Microsoft Azure) Exam is a certification that validates a professional's knowledge and skills in designing and implementing data solutions on Microsoft Azure. DP-203 exam measures an individual's ability to perform tasks such as data storage, processing, and security using Azure technologies. To pass DP-203 exam, candidates must have a comprehensive understanding of Azure data services, including Azure Data Factory, Azure SQL Database, and Azure Cosmos DB.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q132-Q137):

NEW QUESTION # 132
You are planning the deployment of Azure Data Lake Storage Gen2.
You have the following two reports that will access the data lake:
Report1: Reads three columns from a file that contains 50 columns.
Report2: Queries a single record based on a timestamp.
You need to recommend in which format to store the data in the data lake to support the reports. The solution must minimize read times.
What should you recommend for each report? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://streamsets.com/documentation/datacollector/latest/help/datacollector/UserGuide/Destinations/ADLS-G2-D.html

NEW QUESTION # 133
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.

Answer:

Explanation:

Explanation
Table Description automatically generated

Box 1: PARTITION
RANGE RIGHT FOR VALUES is used with PARTITION.
Part 2: [TransactionDateID]
Partition on the date column.
Example: Creating a RANGE RIGHT partition function on a datetime column The following partition function partitions a table or index into 12 partitions, one for each month of a year's worth of values in a datetime column.
CREATE PARTITION FUNCTION [myDateRangePF1] (datetime)
AS RANGE RIGHT FOR VALUES ('20030201', '20030301', '20030401',
'20030501', '20030601', '20030701', '20030801',
'20030901', '20031001', '20031101', '20031201');
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-partition-function-transact-sql

NEW QUESTION # 134
You have an Azure subscription that contains a logical Microsoft SQL server named Server1. Server1 hosts an Azure Synapse Analytics SQL dedicated pool named Pool1.
You need to recommend a Transparent Data Encryption (TDE) solution for Server1. The solution must meet the following requirements:
Track the usage of encryption keys.
Maintain the access of client apps to Pool1 in the event of an Azure datacenter outage that affects the availability of the encryption keys.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/security/workspaces-encryption
https://docs.microsoft.com/en-us/azure/key-vault/general/logging

NEW QUESTION # 135
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 Standard cluster for the data engineers, and a High Concurrency cluster for the jobs.
Does this meet the goal?

A. No
B. Yes

Answer: A

Explanation:
We need a High Concurrency cluster for the data engineers and 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 # 136
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:

Explanation

NEW QUESTION # 137
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Free PDF DP-203 VCE Exam Simulator–The Best Flexible Testing Engine for DP-203 - Authoritative Test DP-203 Discount Voucher

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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q132-Q137):

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