Try Microsoft : DP-900 valid & accurate questions and answers

Last Updated: Aug 20, 2026

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How to book the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Step 1: Visit Microsoft Learning and search for DP-900: Microsoft Azure fundamentals.
  • Step 2: Sign up/log in to the Pearson VUE account
  • Step 3: Select a local center based on your country, date, time and confirm with a payment method.

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

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What job roles can you pursue after passing the Microsoft DP-900 exam?

Microsoft Certified: Azure Data Fundamentals is an entry-level certificate. However, the candidates who pass the prerequisite exam and obtain this certification can pursue a variety of rewarding job roles. These include an IT Administrator, a Desktop Engineer, a Windows Administrator, an Azure Security Engineer, an Azure Solutions Architect, an Azure Application Architect, a Technical Help Desk, and an IT Service Desk Analyst, among others. The salary outlook for these positions is an average of $56,000 per annum.

Microsoft DP-900 Exam Syllabus Topics:

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