Exam DP-900 Microsoft Azure Data Fundamentals Practice Tests
Exam DP-900 Microsoft Azure Data Fundamentals Practice Tests
DESCRIPTION
The "Exam DP-900: Microsoft Azure Data Fundamentals Practice Tests" course is a robust preparatory course for those planning to take the DP-900 certification exam. This exam, organized by Microsoft, is a fundamental stepping stone for any individual seeking a career in data management and data analytics in the Microsoft Azure ecosystem.
This course has been meticulously designed to provide a comprehensive series of practice tests that closely emulate the actual exam. Covering core data concepts, how to work with relational and non-relational data on Azure, and an understanding of analytics workloads on Azure, these practice tests ensure you are well-prepared to tackle all aspects of the DP-900 exam.
Each practice test question comes with a detailed explanation, providing you with an understanding of why a particular answer is correct. This reinforces the fundamental principles and concepts you'll need to master for the exam.
Notably, the course doesn't require a background in data science or related fields. Whether you are an IT professional seeking to upskill, a developer aspiring to transition into data roles, or a student entering the field, this course provides an excellent opportunity to measure your readiness for the DP-900 exam and to gain confidence before sitting for the actual test.
By choosing the "Exam DP-900: Microsoft Azure Data Fundamentals Practice Tests" course, you're preparing yourself to make significant strides in the Azure data landscape, getting one step closer to certification and the numerous career opportunities that come with it.
The scope of the exam:
Describe ways to represent data
Identify options for data storage
Describe common data workloads
Identify roles and responsibilities for data workloads
Describe relational concepts
Describe relational Azure data services
Describe capabilities of Azure storage
Describe capabilities and features of Azure Cosmos DB
Describe common elements of large-scale analytics
Describe consideration for real-time data analytics
Describe data visualization in Microsoft Power BI