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What is the duration, language, and format of Microsoft DP-900: Microsoft Azure Data Fundamentals Exam

  • Number of Questions: 40 to 60 questions (Since Microsoft does not publish this information, the number of exam questions may change without notice.)
  • Length of Examination: 50 mins
  • This is the beta exam, would be available on or around March 31, 2020.
  • Language: English
  • Type of Questions: This test format is multiple choice.
  • Passing score: 700 / 1000

Explain Analytics Workloads on Azure: 25-30%

  • 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 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.
  • 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 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.

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Microsoft DP-900 Korean Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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.
Topic 4
  • 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.

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

Helpful Training Course for Acing DP-900

To help students get fully ready for DP-900, Microsoft has created an official 1-day teacher-guided program for students named ‘Course DP-900T00-A: Microsoft Azure Data Fundamentals’. There are 4 modules in this course which will address all the topics needed for the Microsoft DP-900. However, such a class does not have any related lab exercises, meaning students will not get the scope for applying the things they have learnt in theory. In general, this training is perfect for those who want to learn the main concepts and skills needed to provide cloud data services with the help of Microsoft Azure.

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