Microsoft DP-900 Deutsch Q&A - in .pdf

  • DP-900 Deutsch pdf
  • Exam Code: DP-900 Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Updated: Aug 15, 2026
  • Q & A: 332 Questions and Answers
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  • DP-900 Deutsch Testing Engine
  • Exam Code: DP-900 Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Updated: Aug 15, 2026
  • Q & A: 332 Questions and Answers
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Explain the Techniques Involved in Working with Non-Relational Data on Microsoft Azure: 25-30%

  • Explain Offerings of Non-Relational Data on Azure: The individuals need to have competence in explaining Azure Table storage, Azure File storage, Azure data service for non-relational workloads, Azure Blob Storage, and Azure Cosmos DB APIs.
  • Explain Non-Relational Data Workloads: The candidates should be able to explain the attributes of non-relational data and types of NoSQL and non-relational data. They need to have expertise in recommending the appropriate data stores and establishing them to utilize non-relational data.
  • Identify the Fundamental Management Functions for Non-Relational Data: The examinees should have competence in explaining deployment and provisioning of non-relational data and the techniques for deployment. They also need the skills in identifying the components of data security, fundamental connectivity issues, and non-relational data management tools.

The DP-900: Microsoft Azure Data Fundamentals exam is designed for the individuals pursuing the Microsoft Certified: Azure Data Fundamentals certification. This test evaluates their foundational knowledge of core concepts of data and how these are implemented with the use of Microsoft Azure data services. The associated certificate is an ideal choice for those professionals who want to start a career in the IT field with the main focus on working with data in Cloud. The successful candidates with this certification can continue their journey by earning more advanced options such as Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Azure Database Administrator Associate. However, it is important to mention that this exam is not a requirement for any of these certificates.

This is a foundational certification exam, so it does not require any prerequisites. However, the potential candidates should have a good knowledge of the concepts of non-relational and relational data as well as different categories of data workloads, including analytical and transactional.

The Microsoft DP-900 (Microsoft Azure Data Fundamentals) is the single exam students will have to overcome if they want to attain the Microsoft Certified: Azure Data Fundamentals certificate. Those who hold this certification can become a developer, data engineer, data administrator, or data analyst.

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

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Microsoft DP-900 Practice Test Questions, Microsoft DP-900 Exam Practice Test Questions

The Microsoft DP-900 exam is a qualifying test for obtaining the Microsoft Certified: Azure Data Fundamentals certification. This exam is intended for the entry-level professionals looking to take up a career path in the IT field. Although it is not a requirement for any advanced-level certificate, the DP-900: Microsoft Azure Data Fundamentals test is a great foundation to prepare the individuals for other Azure role-based options. Thus, the certified candidates can pursue two certifications: Azure Data Engineer Associate or Azure Database Administrator Associate.

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Microsoft DP-900 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Describe core data concepts25–30%- Describe data workloads
  • 1. Analytical workloads
    • 2. Transactional workloads
      • 3. Batch and streaming data
        - 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 an analytics workload on Azure25–30%- Describe big data and analytics concepts
              • 1. Data lakes and data warehouses
                • 2. Data ingestion and processing
                  • 3. Modern data warehouse architecture
                    - Describe Azure analytics services
                    • 1. Azure Databricks
                      • 2. Azure Synapse Analytics
                        • 3. Azure Data Lake Storage Gen2
                          • 4. Microsoft Fabric
                            • 5. Azure HDInsight
                              - 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 considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                                      • 1. Consistency levels and partitioning
                                        • 2. Capabilities and features
                                          • 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. Table Storage
                                                  • 2. File Storage
                                                    • 3. Blob Storage
                                                      • 4. Queue Storage
                                                        Identify considerations for relational data on Azure20–25%- Describe relational data concepts
                                                        • 1. Query data with SQL
                                                          • 2. Relationships, keys, constraints
                                                            • 3. Normalization
                                                              - Describe Azure relational data services
                                                              • 1. Open-source databases: PostgreSQL, MySQL, MariaDB
                                                                • 2. SQL Server on Azure Virtual Machines
                                                                  • 3. Azure SQL Managed Instance
                                                                    • 4. Azure SQL Database
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