Microsoft : DP-900 Questions & Answers

Last Updated: Oct 04, 2026

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Exam DP-900: Microsoft Azure Data Fundamentals

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

This exam is intended for candidates beginning to work with data in the cloud.

Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.

Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure Data Fundamentals

Download exam skills outline

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How to operate with non-relational data on Azure

The main concepts covered in this domain include:

  • Non relation data workloads – this sub-section mostly emphasizes the features of non-relational data, when to use it, one's knowledge of the variants of NoSQL and non-relational data, and the ability to choose and recommend appropriate data store.
  • Core administration tasks – this sub-domain covers the processes of deployment and provisioning when it comes to non-relational data, data security, diverse tools for management, and defining the issues with connectivity.
  • Offerings non-relational data on Azure – within this topic, the learner will be conversant with the following in Azure: data services, Cosmos DB APIs, Table storage, Blob storage, File storage.

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

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Microsoft DP-900 Exam Syllabus Topics:

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