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Last Updated: Aug 18, 2026
No. of Questions: 164 Questions & Answers with Testing Engine
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-500
Microsoft Data Platform 500 certification is the most popular certification course in the world. It is a professional level certification of Microsoft and covers the entire Microsoft Data Platform, including SQL Server and Azure.
The DP-500 exam is designed for IT professionals who have at least 12 months of experience implementing data solutions or administering databases. The DP-500 exam requires hands-on experience with designing, developing and implementing enterprise scale analytics solutions using Microsoft technologies such as SQL Server Business Intelligence tools (SSIS, SSAS, SSRS). Our Microsoft DP-500 Exam Questions are prepared by experts in their respective fields and they are designed to cover all the key aspects of the exam. We provide you with real exam questions and answers which will help you in getting good marks in your exam. The main aim of DP-500 Dumps is to help candidates pass their exams on first attempt. This course provides an overview of the key concepts of the DP-500 exam and provides detailed explanations of each topic. It is highly recommended that students take this course before taking their first exam attempt.
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Our Microsoft DP-500 Exam Questions are prepared by experts in their respective fields and they are designed to cover all the key aspects of the exam. We provide you with real exam questions and answers which will help you in getting good marks in your exam. The main aim of DP-500 Dumps is to help candidates pass their exams on first attempt.
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The exam cost of Microsoft DP-500 Certification is $165
Query and transform data (20-25%)
Implement and manage a data analytics environment (25-30%)
Explore and visualize data (20-25%)
Implement and manage data models (25 -30%)
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| Section | Weight | Objectives |
|---|---|---|
| Implement and manage a data analytics environment | 25–30% | - Manage Azure Synapse Analytics workspace and resources
|
| Query and transform data | 20–25% | - Integrate data sources
|
| Implement and manage data models | 25–30% | - Optimize model performance
|
| Explore and visualize data | 20–25% | - Build enterprise-scale reports
|
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