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Explain Analytics Workloads on Azure: 25-30%

  • Explain Data Visualization within Microsoft Power BI: You need to have competence in explaining the function of dashboards, interactive reports, and paginated reporting, as well as the workflow within Power BI.
  • Explain Data Processing & Ingestion on Azure: The learners should be able to explain the fundamental practices for data loading, Azure Data Factory components, and data processing options.
  • Explain Modern Data Warehouse Components: The test takers should understand Azure data services for the latest data warehousing, including Azure Synapse Analytics, Azure HDInsight, Azure Data Lake, and Azure Databricks, as well as explainin the workload and architecture for modern data warehousing.
  • Explain Analytics Workloads: The applicants should be able to explain transactional workloads, data warehousing workloads, and when data warehouse solutions are needed. This subtopic also covers their skills and knowledge associated with the differences between analytics and a transactional workload as well as the differences between real-time and batch.

The Microsoft DP-900 (Microsoft Azure Data Fundamentals) is the single exam students will have to overcome if they want to attain the Microsoft Certified: Azure Data Fundamentals certificate. Those who hold this certification can become a developer, data engineer, data administrator, or data analyst.

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

Microsoft DP-900 Korean Exam Syllabus Topics:

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

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