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Microsoft Azure Data Fundamentals : DP-900 Exam

DP-900 Exam Questions
  • Exam Code: DP-900
  • Exam Name: Microsoft Azure Data Fundamentals
  • Updated: Sep 20, 2026
  • Q & A: 332 Questions and Answers
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What is the duration, language, and format of Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • This is the beta exam, would be available on or around March 31, 2020.
  • Number of Questions: 40 to 60 questions (Since Microsoft does not publish this information, the number of exam questions may change without notice.)
  • Language: English
  • Type of Questions: This test format is multiple choice.
  • Length of Examination: 50 mins
  • Passing score: 700 / 1000

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DP-900 exam dumps

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  • Europe - 60,547 EURO
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Workload analytics on Azure

  • Elements of a modern data warehouse – this sub-section is focused on Azure data services related to modern data warehousing. In addition, applicants should be familiar with modern data warehousing workload and architecture.
  • Data visualization in Microsoft Power BI – this topic requires candidates to learn more about paginated reporting, dashboards, interactive reports, as well as workflow in Power BI.
  • Analytics workloads – under this topic, candidates should learn more about transactional workloads as well as data warehousing workloads. Also, they have to get skilled in differentiating between an analytics and a transactional workload, know the difference between real and batch time, and be able to determining when a data warehouse solution is required.
  • Date processing and ingestion on Azure – main topics within this subdomain include data loading common practices, Azure Data Factory components (activities, pipeline, etc.), and data processing.

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

Microsoft DP-900 Exam Syllabus Topics:

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

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