Microsoft DP-900 Deutsch Dumps : Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)

DP-900 Deutsch real exams

Exam Code: DP-900-Deutsch

Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)

Updated: Sep 01, 2026

Q & A: 332 Questions and Answers

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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.

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

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

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Microsoft DP-900 Deutsch Exam Syllabus Topics:

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

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