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Explain the Techniques Involved in Working with Non-Relational Data on Microsoft Azure: 25-30%
- Explain Offerings of Non-Relational Data on Azure: The individuals need to have competence in explaining Azure Table storage, Azure File storage, Azure data service for non-relational workloads, Azure Blob Storage, and Azure Cosmos DB APIs.
- Identify the Fundamental Management Functions for Non-Relational Data: The examinees should have competence in explaining deployment and provisioning of non-relational data and the techniques for deployment. They also need the skills in identifying the components of data security, fundamental connectivity issues, and non-relational data management tools.
- Explain Non-Relational Data Workloads: The candidates should be able to explain the attributes of non-relational data and types of NoSQL and non-relational data. They need to have expertise in recommending the appropriate data stores and establishing them to utilize non-relational data.
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Administer infrastructure resources in Azure
Azure Storage
Azure Network
The benefit of obtaining the Microsoft DP-900: Microsoft Azure Data Fundamentals Exam Certification
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
Microsoft DP-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Describe considerations for working with non-relational data on Azure | 15-20% | - Describe non-relational Azure data services
- 1. Describe Azure Table storage
- 2. Describe Azure File storage
- 3. Describe Azure Blob storage
- 4. Describe Azure Cosmos DB
- Describe non-relational concepts
- 1. Identify non-relational data
- 2. Describe non-relational data offerings
|
| Topic 2: Describe an analytics workload on Azure | 25-30% | - Describe Azure data analytics services
- 1. Describe Microsoft Fabric
- 2. Describe Azure Synapse Analytics
- 3. Describe Azure Data Factory
- 4. Describe Azure Databricks
- 5. Describe Azure Stream Analytics
- 6. Describe Azure HDInsight
- Describe analytics concepts
- 1. Describe analytical workloads
- 2. Describe ETL and ELT processes
- 3. Describe transactional workloads
- 4. Describe data warehousing
- Describe data visualization in Microsoft Power BI
- 1. Describe Power BI
- 2. Describe Power BI tools and workflow
- 3. Describe Power BI reports and dashboards
|
| Topic 3: Describe core data concepts | 25-30% | - Describe ways to represent data
- 1. Describe features of unstructured data
- 2. Describe features of semi-structured data
- 3. Describe features of structured data
- Identify options for data storage
- 1. Describe types of databases
- 2. Describe common formats for data files
|
| Topic 4: Identify considerations for relational data on Azure | 20-25% | - Describe relational concepts
- 1. Describe normalization
- 2. Identify features of relational data
- Describe relational Azure data services
- 1. Describe Azure SQL family of products
- 2. Describe Azure Database for MySQL
- 3. Describe Azure SQL Managed Instance
- 4. Describe Azure Database for PostgreSQL
- 5. Describe SQL Server on Azure Virtual Machines
- 6. Describe Azure Database for MariaDB
- 7. Describe Azure SQL Database
|