Microsoft : DP-900 Questions & Answers

Last Updated: Aug 11, 2026

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Introduction to Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

Microsoft Azure Data Fundamentals is an exam that identifies individuals who have the knowledge to work with Azure data storage features. Building on previous core principles of data management, Azure Data Fundamentals exam is designed to evaluate the ability of the candidate. Money designed to assess the skills level for both professionals and students. Determine the type of skills required for a particular situation, for example, a cloud administrator or a data analyst. Gen candidate will have to know the fundamentals of Data Management to work with Azure data storage, create tools to manage data, locate, protect and process it. Relevant topics in a data management environment, a certified candidate should understand. Dml, Db, protection tools through recovery, recovery strategies, documentation data management policies, data loss prevention tools to backup and recovery for backup recovery.

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

How to book the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Step 1: Visit Microsoft Learning and search for DP-900: Microsoft Azure fundamentals.
  • Step 2: Sign up/log in to the Pearson VUE account
  • Step 3: Select a local center based on your country, date, time and confirm with a payment method.

The Microsoft DP-900 exam is intended for candidates who already have foundational knowledge and skills in performing basic tasks and using Microsoft Azure data services. It is also recommended for those who are starting their careers in the field of cloud data. Although there are no strict prerequisites, every individual who desires to take DP-900 test should have familiarity with non-relational and relational data as well as various types of data workloads such as analytical and transactional.

Microsoft DP-900 Exam Syllabus Topics:

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

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