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

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More about DP-900 Exam

In brief, DP-900 test focuses on exam objectives like interacting with relational data on Azure, handling analytics workload on Azure, dealing with non-relational data on Azure, and knowing the central data concepts needed for Azure. The Microsoft DP-900 test, in particular, is designed for those who just started to work with cloud-related data. Those planning to take DP-900 should already possess basic knowledge of the main data-related concepts and understand how those concepts can be deployed with the help of Microsoft Azure data services. Also, candidates for DP-900 should be no strangers to analytical data workloads, transactional data workloads, non-relational data, and relational data. When it comes to the exam details, there are no mandatory prerequisites needed for DP-900. The signup cost of this fundamental-level exam is USD 99, plus it is administered around the globe in countless tongues like Spanish, French, German, Korean, Chinese, Japanese, and English. To know more, DP-900 is conducted at nearby exam centers or on the web in a supervised setting. As it was claimed above, passing this single exam means candidates will be awarded the Microsoft Certified: Azure Data Fundamentals validation, which is renewable. After attaining this certificate, learners can chase higher-level Microsoft certifications in the future like the Microsoft Certified: Azure Data Engineer Associate or the Microsoft Certified: Azure Database Administrator Associate.

Microsoft DP-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Describe core data concepts25-30%- Identify options for data storage
  • 1. Describe common formats for data files
  • 2. Describe types of databases
- Describe ways to represent data
  • 1. Describe features of unstructured data
  • 2. Describe features of semi-structured data
  • 3. Describe features of structured data
Topic 2: Describe an analytics workload on Azure25-30%- Describe analytics concepts
  • 1. Describe data warehousing
  • 2. Describe ETL and ELT processes
  • 3. Describe transactional workloads
  • 4. Describe analytical workloads
- Describe data visualization in Microsoft Power BI
  • 1. Describe Power BI tools and workflow
  • 2. Describe Power BI
  • 3. Describe Power BI reports and dashboards
- Describe Azure data analytics services
  • 1. Describe Azure Data Factory
  • 2. Describe Azure Databricks
  • 3. Describe Azure HDInsight
  • 4. Describe Azure Synapse Analytics
  • 5. Describe Azure Stream Analytics
  • 6. Describe Microsoft Fabric
Topic 3: Describe considerations for working with non-relational data on Azure15-20%- Describe non-relational concepts
  • 1. Identify non-relational data
  • 2. Describe non-relational data offerings
- Describe non-relational Azure data services
  • 1. Describe Azure File storage
  • 2. Describe Azure Blob storage
  • 3. Describe Azure Table storage
  • 4. Describe Azure Cosmos DB
Topic 4: Identify considerations for relational data on Azure20-25%- Describe relational Azure data services
  • 1. Describe Azure SQL Managed Instance
  • 2. Describe Azure Database for MariaDB
  • 3. Describe Azure Database for PostgreSQL
  • 4. Describe SQL Server on Azure Virtual Machines
  • 5. Describe Azure SQL Database
  • 6. Describe Azure SQL family of products
  • 7. Describe Azure Database for MySQL
- Describe relational concepts
  • 1. Identify features of relational data
  • 2. Describe normalization

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