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Microsoft Azure Data Fundamentals (DP-900 Korean Version) : DP-900 Korean Exam

DP-900 Korean Exam Questions
  • Exam Code: DP-900-KR
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: May 31, 2026
  • Q & A: 316 Questions and Answers
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What Are the Exam Topics?

Core data concepts

This topic majorly addresses the following skills:

  • Main concepts of data analytics – data visualization, business intelligence (BI), analytics techniques (diagnostic, predictive, descriptive, cognitive, prescriptive) and basic chart types such as pie charts and bar charts are the main concepts addressed in this category. Also, data processing techniques are covered along with ETL processing.
  • Various data workloads – this involves an overview of the features of relational data as well as the description, similarities and differences between streaming data and batch data as well as.

Microsoft DP-900 Korean Exam Syllabus Topics:

TopicDetails
Topic 1
  • Identify considerations for relational data on Azure: This topic provides aspiring Microsoft data engineers with a clear understanding of relational data concepts, including schemas, tables, keys, and normalization. It further explores relational Azure data services such as Azure SQL Database and Azure Database for MySQL, highlighting their use cases and capabilities.
Topic 2
  • Describe core data concepts: In this topic, aspiring Microsoft data engineers explore fundamental ways to represent data, such as structured, semi-structured, and unstructured formats. Additionally, the topic explains various data storage options, emphasizing file, database, and object storage. It also details common data workloads, including transactional, analytical, and streaming workloads. Lastly, the roles and responsibilities for managing data workloads, such as administrators, engineers, and analysts, are clarified.
Topic 3
  • Describe an analytics workload: This topic introduces aspiring Microsoft data engineers to the components of large-scale analytics, such as data ingestion, transformation, and querying. It also discusses real-time data analytics considerations, including low-latency processing with Azure Stream Analytics. Finally, data visualization with Microsoft Power BI, focusing on interactive dashboards and reports, is covered.
Topic 4
  • Describe considerations for working with non-relational data on Azure: Aspiring Microsoft data engineers gain insight into Azure's non-relational data capabilities in this topic. It discusses Azure Storage options, including Blob, Table, and Queue Storage, suitable for diverse scenarios. Additionally, the features and strengths of Azure Cosmos DB, such as global distribution and multi-model support, are outlined.

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

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