Microsoft DP-900 exam comprises of multiple-choice questions that will test the candidate's knowledge of various data concepts in the Azure environment. DP-900-KR exam is timed and the candidate is given two hours to complete the test. The scoring is done on a scale of 0-1000 and the passing score for the exam is 700.
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Microsoft DP-900, also known as the Microsoft Azure Data Fundamentals Certification Exam, is an entry-level certification exam that validates the basic knowledge and understanding of cloud data services and Azure data services. DP-900-KR exam is designed for individuals who are interested in pursuing a career in data and want to demonstrate their competence in Azure data services. DP-900-KR exam is ideal for aspiring data analysts, data scientists, data engineers, or data architects who are looking to validate their knowledge and skillset in Azure data services.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
The Microsoft DP-900-KR exam is ideal for data professionals, database administrators, and business intelligence developers who want to gain a fundamental understanding of Azure data services. It is also suitable for individuals who are interested in learning how to use Azure data services to solve business problems and improve decision-making processes.
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Microsoft DP-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Identify considerations for relational data on Azure | 20–25% | - Describe Azure relational data services
- 1. SQL Server on Azure Virtual Machines
- 2. Open-source databases: PostgreSQL, MySQL, MariaDB
- 3. Azure SQL Managed Instance
- 4. Azure SQL Database
- Describe relational data concepts
- 1. Normalization
- 2. Query data with SQL
- 3. Relationships, keys, constraints
|
| Topic 2: Describe considerations for working with non-relational data on Azure | 15–20% | - Describe non-relational data concepts
- 1. Use cases for non-relational data
- 2. Characteristics of NoSQL data
- Describe Azure storage services
- 1. File Storage
- 2. Blob Storage
- 3. Table Storage
- 4. Queue Storage
- Describe Azure Cosmos DB
- 1. APIs and data models
- 2. Consistency levels and partitioning
- 3. Capabilities and features
|
| Topic 3: Describe an analytics workload on Azure | 25–30% | - Describe data visualization
- 1. Power BI capabilities
- 2. Data models and reports
- Describe big data and analytics concepts
- 1. Data lakes and data warehouses
- 2. Data ingestion and processing
- 3. Modern data warehouse architecture
- Describe Azure analytics services
- 1. Azure Databricks
- 2. Microsoft Fabric
- 3. Azure Data Lake Storage Gen2
- 4. Azure Synapse Analytics
- 5. Azure HDInsight
- Describe real-time analytics
- 1. Azure Stream Analytics
- 2. Stream processing concepts
|
| Topic 4: Describe core data concepts | 25–30% | - Describe types of data
- 1. File formats
- 2. Structured, semi-structured, and unstructured data
- Describe data workloads
- 1. Transactional workloads
- 2. Analytical workloads
- 3. Batch and streaming data
- Describe roles and responsibilities
- 1. Data engineer, data analyst, database administrator
|