Prepare with Microsoft DP-900 exam practice material, pass for sure

Updated: Aug 21, 2026

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DP-900 Practice Q&A's

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Explain the Techniques Involved in Working with Relational Data on Microsoft Azure: 25-30%

  • Identify the Fundamental Management Tasks for Relational Data: The applicants should be able to explain the deployment and provisioning of relational data services. They also need to understand the techniques for deployment, such as Azure Resource Manager templates, Azure portal, Azure CLI, and Azure PowerShell. In addition, the students should be able to identify the fundamental connectivity issues and components of data security.
  • Explain the Query Methods for Data with the SQL Language: The learners should be capable of comparing the Data Manipulation Language with the Data Definition Language. They should also be able to query relational data within Azure Database for MySQL, Azure SQL Database, and Azure Database for PostgreSQL.
  • Explain the Concepts of Relational Data Workloads: The examinees should be able to explain the structures of relational data and identify the appropriate data for relational workloads.
  • Explain Relational Azure Data Services: The individuals should have the ability to explain and compare SaaS, PaaS, and IaaS solutions as well as Azure Synapse Analytics. They also need the knowledge of Azure SQL database services, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure Database for MariaDB.

Skills measured

  • Describe core data concepts (15-20%)
  • Describe how to work with relational data on Azure (25-30%)
  • Describe an analytics workload on Azure (25-30%)
  • Describe how to work with non-relational data on Azure (25-30%)

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

Microsoft Azure Data Fundamentals Exam Certification Details:

Exam NameMicrosoft Certified - Azure Data Fundamentals
Schedule ExamPearson VUE
Books / TrainingDP-900T00-A: Microsoft Azure Data Fundamentals
Passing Score700 / 1000
Number of Questions40-60
Sample QuestionsMicrosoft Azure Data Fundamentals Sample Questions
Exam Price$99 (USD)
Duration60 mins
Exam CodeDP-900

Microsoft DP-900 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure Data Fundamentals
Exam Number:DP-900
Available Languages:English, Japanese, Chinese (Simplified), Korean, French, German, Spanish, Portuguese (Brazil), Russian, Indonesian, Arabic, Chinese (Traditional)
Exam Duration:60 minutes
Real Exam Qty:40–60
Exam Format:Multiple choice, Multiple select, Drag-and-drop, Scenario-based questions
Exam Price:$99 USD
Passing Score:700 / 1000
Related Certifications:Azure Database Administrator Associate
Azure Data Engineer Associate
Azure Data Scientist Associate
Certificate Validity Period:Lifetime
Recommended Training:DP-900T00: Microsoft Azure Data Fundamentals
Microsoft Learn Free Learning Path
Exam Registration:Certiport (for students/educators)
Pearson VUE
Sample Questions:Microsoft DP-900 Sample Questions
Exam Way:Online proctored or onsite at authorized test centers
Pre Condition:No prerequisites required
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-900

Microsoft DP-900 Exam Syllabus Topics:

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

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