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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.

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

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Microsoft DP-900 Exam Syllabus Topics:

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

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