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Microsoft DP-900 Deutsch Braindumps - in .pdf Free Demo

  • Exam Code: DP-900-Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Last Updated: Aug 13, 2026
  • Q & A: 332 Questions and Answers
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  • Exam Code: DP-900-Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Last Updated: Aug 13, 2026
  • Q & A: 332 Questions and Answers
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Topics of Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Describe how to work with relational data on Azure (25-30%)
  • Describe how to work with non-relational data on Azure (25-30%)
  • Describe core data concepts (15-20%)
  • Describe an analytics workload on Azure (25-30%)

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

Exam Details

The Microsoft DP-900 exam has the following features:

  • It costs $99. As for the job seekers impacted by the pandemic (COVID -19), they can schedule their exam for just $15.
  • The number of questions is not disclosed but you should expect 40-60 items
  • The registration for the test is done at Pearson VUE for non-students who are interested in technology and via Certiport for students or instructors.

Upon passing DP-900, you will earn the Microsoft Certified: Azure Data Fundamentals. It showcases that you have the foundational knowledge on core data concepts and how they can be implemented using Microsoft Azure. Note that Microsoft DP-900 will be updated on January 27, 2021.

Microsoft DP-900 Deutsch Exam Syllabus Topics:

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

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