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Microsoft Microsoft Certified: Azure Data Fundamentals DP-900

DP-900

Exam Code: DP-900

Exam Name: Microsoft Azure Data Fundamentals

Updated: Aug 18, 2026

Q & A: 332 Questions and Answers

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About Microsoft DP-900 Exam

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Certification Paths Available

Upon earning Microsoft Certified: Azure Data Fundamentals, you will be able to advance your career to higher-level certifications. For instance, it can be a starting point for Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Azure Database Administrator Associate. However, this fundamental accreditation is not a requirement for earning any of the next certificates. Therefore, all you have to do is to pass Microsoft DP-900 exam and prepare to face the real-world challenges as you advance in your career.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900

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The benefit of obtaining the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam Certification

The Microsoft DP-900: Microsoft Azure Data Fundamentals Exam is a valuable asset to networking professionals. With this certification, one will have the ability to get a job with the industry. The certification will provide work experience and skills that are directly related with the industry. Fields of work that require this certification are Business Intelligence and Data Warehousing. Life of a certified individual is filled with great opportunities and success if the individual is talented and passionate. Flow of work for this certification is continuous and increasing. Beginner and experienced persons can get jobs and skill development through this certification. Covering this certification will enhance knowledge and understanding of Business Intelligence and Data Warehousing. Explorer and quick learner can also take the benefit of this certification. Email, instant messaging, chat and news details will be helpful in this certification. Scenario based questions are also beneficial in this certificate. Computers and emailing and social media and internet applications will be useful in this certification. Code lines and QR code and data tables will be helpful in this certification. Desktop and laptops and monitors and tablets and projectors will be helpful in this certification. Microsoft DP-900 exam dumps can help you pass exam in first try. Template questions will help you cover most of the exam area. Computer and devices and devices and servers, they help you memorize the most important concepts in the exam. Ssms and docs and spms and email, they help you understand the online learning portal. Testing and assessment and practice questions, they help you learn the most important material to study. Paginated and dynamic and interactive and live, they are the best practice guides to learn for the exam. Bar and charts and tables and flowcharts, they help you understand the concepts in the best possible manner. Objectives and scenarios and results and prerequisites, they help you learn the concepts deeply.

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What should you know about the Microsoft DP-900 exam?

The Microsoft DP-900 exam is 60 minutes long and consists of 40-60 questions of various types. Some of these formats may include multiple choice, active screen, drag and drop, build list, best answer, short answer, and case studies, among others. The candidates can find the examples of these question types on the official website. This certification test is designed to evaluate the competence of the professionals in using non-relational and relational data on Azure, as well as the analytics workload that is available on Azure. The exam fee is $99 and the applicants must pay it before registering for and scheduling their test. To complete this exam on the first try, they must achieve at least 720 points on a scale of 100-1000. The languages available for this test include English, German, Korean, Spanish, French, Japanese, and Simplified Chinese.

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Microsoft DP-900 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Identify considerations for relational data on Azure20–25%- Describe Azure relational data services
  • 1. Azure SQL Database
    • 2. SQL Server on Azure Virtual Machines
      • 3. Azure SQL Managed Instance
        • 4. Open-source databases: PostgreSQL, MySQL, MariaDB
          - Describe relational data concepts
          • 1. Normalization
            • 2. Relationships, keys, constraints
              • 3. Query data with SQL
                Topic 2: Describe an analytics workload on Azure25–30%- Describe Azure analytics services
                • 1. Azure Data Lake Storage Gen2
                  • 2. Microsoft Fabric
                    • 3. Azure HDInsight
                      • 4. Azure Databricks
                        • 5. Azure Synapse Analytics
                          - Describe real-time analytics
                          • 1. Azure Stream Analytics
                            • 2. Stream processing concepts
                              - Describe data visualization
                              • 1. Power BI capabilities
                                • 2. Data models and reports
                                  - Describe big data and analytics concepts
                                  • 1. Data lakes and data warehouses
                                    • 2. Modern data warehouse architecture
                                      • 3. Data ingestion and processing
                                        Topic 3: Describe considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                                        • 1. Capabilities and features
                                          • 2. Consistency levels and partitioning
                                            • 3. APIs and data models
                                              - Describe non-relational data concepts
                                              • 1. Characteristics of NoSQL data
                                                • 2. Use cases for non-relational data
                                                  - Describe Azure storage services
                                                  • 1. Blob Storage
                                                    • 2. Table Storage
                                                      • 3. File Storage
                                                        • 4. Queue Storage
                                                          Topic 4: Describe core data concepts25–30%- Describe roles and responsibilities
                                                          • 1. Data engineer, data analyst, database administrator
                                                            - Describe data workloads
                                                            • 1. Batch and streaming data
                                                              • 2. Analytical workloads
                                                                • 3. Transactional workloads
                                                                  - Describe types of data
                                                                  • 1. Structured, semi-structured, and unstructured data
                                                                    • 2. File formats

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