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Microsoft DP-203 Practice Test
Are you ready to explore your self on Microsoft DP-203!!
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Online - Self Paced
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About Microsoft DP-203 Practice Test
MICROSOFT DP-203: DATA ENGINEERING WITH AZURE DATA FACTORY
Microsoft's DP-203 course is designed to provide comprehensive training in using
Azure Data Factory
to manage and organize data in the Azure cloud. This course equips students with the skills to design, deploy, and monitor data pipelines using
Azure Data Factory
, covering key concepts and hands-on experience.
COURSE CONTENT
Participants will learn how to:
Build and Manage Data Pipelines
– Create, configure, and optimize data workflows within Azure Data Factory.
Manage Data Flow Activities
– Implement transformations, control data flow, and ensure efficient data movement.
Configure Trigger Events
– Automate data pipelines with time-based and event-driven triggers.
Integrate Data Using Azure Services
– Work with Azure Data Lake, Azure Synapse Analytics, and other Azure services for seamless data integration. The course starts with an introduction to
Azure Data Factory
and its integration with Azure services, followed by deep dives into data engineering best practices. Students will gain practical experience through hands-on labs and real-world projects.
LEARNING OUTCOMES
By the end of the course, students will have a thorough understanding of how to use
Azure Data Factory
for data engineering projects. The training includes interactive labs and exercises to reinforce learning and application of concepts.
CERTIFICATION EXAM DETAILS
The
Microsoft DP-203 exam
consists of
40-60 questions
covering topics such as
Azure Active Directory, Azure Data Factory, Azure Data Lake, Azure Data Services
, and more. The exam features multiple-choice, drag-and-drop, and fill-in-the-blank questions. Candidates have
130 minutes
to complete the exam, and a passing score of
700 or higher
is required. Successfully passing the DP-203 exam validates an individual's expertise in
data engineering on Microsoft Azure
, making them a valuable asset in cloud-based data management and analytics.