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What should you know about the Microsoft DP-900 exam?

The Microsoft DP-900 exam is 60 minutes long and consists of 40-60 questions of various types. Some of these formats may include multiple choice, active screen, drag and drop, build list, best answer, short answer, and case studies, among others. The candidates can find the examples of these question types on the official website. This certification test is designed to evaluate the competence of the professionals in using non-relational and relational data on Azure, as well as the analytics workload that is available on Azure. The exam fee is $99 and the applicants must pay it before registering for and scheduling their test. To complete this exam on the first try, they must achieve at least 720 points on a scale of 100-1000. The languages available for this test include English, German, Korean, Spanish, French, Japanese, and Simplified Chinese.

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

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The Microsoft DP-900 test evaluates the ability of the candidates to execute specific technical tasks. The examinees must understand these areas before they take this test. The topics that this certification exam covers are as follows:

Explain the Concepts of Core Data: 15-20%

  • Explain Core Data Workloads Types: The test takers should be able to explain batch data, attributes of relational data, streaming data, and the differences between streaming and batch data.
  • Explain the Core Concepts of Data Analytics: The candidates need to be able to explain data visualization, analytics techniques, data processing concepts, ETL and ELT processing, as well as the basic types of charts, including pie charts and bar charts.

Microsoft DP-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Identify considerations for relational data on Azure20–25%- Describe relational data concepts
  • 1. Normalization
    • 2. Relationships, keys, constraints
      • 3. Query data with SQL
        - Describe Azure relational data services
        • 1. SQL Server on Azure Virtual Machines
          • 2. Azure SQL Managed Instance
            • 3. Open-source databases: PostgreSQL, MySQL, MariaDB
              • 4. Azure SQL Database
                Topic 2: Describe core data concepts25–30%- Describe roles and responsibilities
                • 1. Data engineer, data analyst, database administrator
                  - Describe data workloads
                  • 1. Batch and streaming data
                    • 2. Transactional workloads
                      • 3. Analytical workloads
                        - Describe types of data
                        • 1. Structured, semi-structured, and unstructured data
                          • 2. File formats
                            Topic 3: Describe considerations for working with non-relational data on Azure15–20%- Describe non-relational data concepts
                            • 1. Use cases for non-relational data
                              • 2. Characteristics of NoSQL data
                                - Describe Azure Cosmos DB
                                • 1. Consistency levels and partitioning
                                  • 2. Capabilities and features
                                    • 3. APIs and data models
                                      - Describe Azure storage services
                                      • 1. Table Storage
                                        • 2. Queue Storage
                                          • 3. Blob Storage
                                            • 4. File Storage
                                              Topic 4: Describe an analytics workload on Azure25–30%- 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 Azure analytics services
                                                        • 1. Microsoft Fabric
                                                          • 2. Azure Synapse Analytics
                                                            • 3. Azure HDInsight
                                                              • 4. Azure Databricks
                                                                • 5. Azure Data Lake Storage Gen2
                                                                  - Describe data visualization
                                                                  • 1. Power BI capabilities
                                                                    • 2. Data models and reports

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