DP-900 Korean Q&As - in .pdf

DP-900 Korean pdf
  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Jul 21, 2026
  • Q & A: 320 Questions and Answers
  • PDF Price: $69.99
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  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Jul 21, 2026
  • Q & A: 320 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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DP-900 Korean Desktop Testing Engine

DP-900 Korean Testing Engine
  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Jul 21, 2026
  • Q & A: 320 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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For more info read reference:

Microsoft learning site Administer infrastructure resources in Azure Azure Storage Azure Network

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

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Microsoft DP-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
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
              Describe an analytics workload on Azure25–30%- Describe data visualization
              • 1. Power BI capabilities
                • 2. Data models and reports
                  - Describe Azure analytics services
                  • 1. Azure Data Lake Storage Gen2
                    • 2. Azure Databricks
                      • 3. Azure Synapse Analytics
                        • 4. Microsoft Fabric
                          • 5. Azure HDInsight
                            - Describe real-time analytics
                            • 1. Azure Stream Analytics
                              • 2. Stream processing concepts
                                - Describe big data and analytics concepts
                                • 1. Modern data warehouse architecture
                                  • 2. Data lakes and data warehouses
                                    • 3. Data ingestion and processing
                                      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. Azure SQL Managed Instance
                                              • 2. Open-source databases: PostgreSQL, MySQL, MariaDB
                                                • 3. SQL Server on Azure Virtual Machines
                                                  • 4. Azure SQL Database
                                                    Describe considerations for working with non-relational data on Azure15–20%- 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. File Storage
                                                              • 3. Blob Storage
                                                                • 4. Queue Storage
                                                                  - Describe non-relational data concepts
                                                                  • 1. Characteristics of NoSQL data
                                                                    • 2. Use cases for non-relational data

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