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

  • Exam Code: DP-900-Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Updated: Aug 06, 2026
  • Q & A: 320 Questions and Answers

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The candidates for the Microsoft DP-900 test will be measured in a variety of technical skill areas. These domains are divided into several topics. It is recommended that the applicants review the exam topics in detail and choose the appropriate study materials to prepare for the test. Below are the highlights of the objectives covered in this certification exam:

  • Explain Analytics Workloads on Azure: 25-30%

    This domain of the DP-900 exam measures one’s knowledge of analytics workloads, data processing, and ingestion on Azure, as well as the elements of modern data warehouses. The candidates will also be tested on their understanding of data visualization within Microsoft Power BI. This involves describing the specific role of dashboards, paginated reporting, interactive reports, and workflows in Power BI.

  • Explain how Non-Relational Data Works on Azure: 25-30%

    The questions from this section will evaluate the understanding of the candidates in non-relational data workloads as well as non-relational data contributions on Azure. They must be able to explain Azure File storage, Azure Cosmos DB APIs, Azure Blob Storage, and Azure Table storage. They should also be able to identify the foundational management tasks for non-relational data.

  • Explain how Relational Data Works on Azure: 25-30%

    The test takers will be required to have the ability to describe some concepts in this topic, including relational data workloads and relational Azure data services. They will also need to know how to identify the basic management functions for relational data. Additionally, they need to possess a good understanding of how to use the SQL language to describe the query methods for data.

  • Explain the Concepts of Core Data: 15-20%

    Within this subject area, the students should be able to explain different categories of core data workloads that are available. To answer questions from this subtopic, the examinees should be able to explain batch data and streaming data. They should also know the attributes of relational data and core differences between streaming and batch data. It also covers their skills in core concepts of data analytics. This requires an understanding of data visualization, basic chart types, analytics techniques, data processing concepts, as well as ETL & ELT processing.

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

How to operate with relational data on Azure

Here, the candidate should be equipped with knowledge and skills in the following sub domains:

  • Identification of basic management roles for relational data – under this sub domain there are several skills covered that include the deployment and provisioning of relational data, various deployment methods such as Azure Resource Manager templates, Azure portal, Azure command-line interface (CLI), etc. Also, one should be knowledgeable in data components identification (authentication and firewall), the identification of basic connectivity problems such as accessing Azure VNets, firewalls, access from the internet and authentication). One more knowledge area involved is query tools (SQL Management Studio, Azure Data Studio, utility, sqlcmd etc.).
  • Relational Azure data services – this section of the exam is focused on the following: the understanding of IaaS, SaaS and PaaS solutions and their comparison, Azure SQL DB services such as Azure SQL managed instance and Azure virtual machine, Azure Synapse Analytics, and Azure Database for MariaDB, PostgreSQL and for MySQL.
  • Data querying techniques that require utilizing SQL language – it deals with the Data Manipulation Language (DML) and Data Definition Language (DDL) as well as querying relational data on Azure SQL DB.
  • Relational data workloads – the candidate has to gain skills in identifying the appropriate data offerings when it comes to relational workload and learn more about structures of relational data.

Microsoft DP-900 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Describe considerations for working with non-relational data on Azure15-20%- Describe non-relational Azure data services
  • 1. Describe Azure File storage
  • 2. Describe Azure Blob storage
  • 3. Describe Azure Cosmos DB
  • 4. Describe Azure Table storage
- Describe non-relational concepts
  • 1. Describe non-relational data offerings
  • 2. Identify non-relational data
Describe core data concepts25-30%- Identify options for data storage
  • 1. Describe types of databases
  • 2. Describe common formats for data files
- Describe ways to represent data
  • 1. Describe features of semi-structured data
  • 2. Describe features of unstructured data
  • 3. Describe features of structured data
Describe an analytics workload on Azure25-30%- Describe data visualization in Microsoft Power BI
  • 1. Describe Power BI reports and dashboards
  • 2. Describe Power BI
  • 3. Describe Power BI tools and workflow
- Describe Azure data analytics services
  • 1. Describe Azure HDInsight
  • 2. Describe Azure Databricks
  • 3. Describe Azure Stream Analytics
  • 4. Describe Azure Synapse Analytics
  • 5. Describe Azure Data Factory
  • 6. Describe Microsoft Fabric
- Describe analytics concepts
  • 1. Describe data warehousing
  • 2. Describe ETL and ELT processes
  • 3. Describe analytical workloads
  • 4. Describe transactional workloads
Identify considerations for relational data on Azure20-25%- Describe relational concepts
  • 1. Identify features of relational data
  • 2. Describe normalization
- Describe relational Azure data services
  • 1. Describe Azure SQL Database
  • 2. Describe Azure SQL Managed Instance
  • 3. Describe Azure Database for MariaDB
  • 4. Describe Azure Database for MySQL
  • 5. Describe Azure Database for PostgreSQL
  • 6. Describe SQL Server on Azure Virtual Machines
  • 7. Describe Azure SQL family of products

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