Microsoft Azure Data Fundamentals (DP-900) Exam Questions
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The Microsoft DP-900 exam is designed for professionals who want to improve their skills in Microsoft Azure Data Fundamentals technology. This Beginner certification checks your understanding of the main concepts, tools, and best practices. It also tests your ability to use Microsoft Azure SQL Database, MySQL in real work situations.
The Microsoft Azure Data Fundamentals certification can be a valuable step toward building a strong foundation for your IT career. It helps employers recognize your abilities and gives you a better chance of finding new job opportunities. This certification also helps you stay up-to-date with the latest Microsoft Azure Data Fundamentals exam technologies, tools, and industry standards.
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Stand Out to Hiring Managers
The Microsoft DP-900 certification exam can help demonstrate your knowledge and skills, giving hiring managers a clearer view of your professional capabilities.
Build a Case for Promotions
The Microsoft DP-900 certification can help you demonstrate your skills, strengthen your professional profile, and prepare for new career opportunities.
Higher Job Security
A Microsoft Azure Data Fundamentals credential raises your value, commands higher pay, and makes you hard to replace.
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Microsoft DP-900 Exam Domains & Weightage
Microsoft DP-900 Exam Details (Official)
| Vendor | Microsoft |
| Exam Code | DP-900 |
| Exam Name | Microsoft Azure Data Fundamentals |
| Certification | Microsoft Azure |
| Exam Duration | 45 Minutes |
Microsoft Azure Data Fundamentals Exam Objectives
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1
1.0 Describe core data concepts (25-30%)
- 1.1Describe ways to represent data
- 1.2Describe the features of structured data
- 1.3Describe the features of semi-structured data
- 1.4Describe the features of unstructured data
- 1.5Identify options for data storage
- 1.6Describe common formats for data files
- 1.7Describe features of common data stores including databases
- 1.8Identify Azure datastores for common use cases
- 1.9Describe common data workloads
- 1.10Describe features of transactional workloads
- 1.11Describe features of analytical workloads
- 1.12Identify roles and responsibilities for data workloads
- 1.13Describe responsibilities for database administrators
- 1.14Describe responsibilities for data engineers
- 1.15Describe responsibilities for data analysts
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2
2.0 Identify considerations for relational data on Azure (20-25%)
- 2.1Describe relational concepts
- 2.2Identify features of relational data
- 2.3Describe normalization and why it is used
- 2.4Identify common structured query language (SQL) statements
- 2.5Identify common database objects
- 2.6Describe relational Azure data services
- 2.7Describe the Azure SQL family of products, including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
- 2.8Identify Azure database services for open-source database systems
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3
3.0 Describe considerations for working with non-relational data on Azure (15-20%)
- 3.1Describe the capabilities of Azure storage
- 3.2Describe features of Azure Blob storage
- 3.3Describe features of Azure Files
- 3.4Describe features of Azure Table storage
- 3.5Describe the capabilities and features of Azure Cosmos DB
- 3.6Identify use cases for Azure Cosmos DB
- 3.7Describe Azure Cosmos DB APIs
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4
4.0 Describe an analytics workload (25-30%)
- 4.1Describe common elements of large-scale analytics
- 4.2Describe considerations for data ingestion and processing
- 4.3Describe options for analytical data stores
- 4.4Describe Microsoft cloud services for large-scale analytics, including Azure Databricks and Microsoft Fabric
- 4.5Describe considerations for real-time data analytics
- 4.6Describe the difference between batch and streaming data
- 4.7Identify Microsoft cloud services for real-time analytics
- 4.8Describe data visualization in Microsoft Power BI
- 4.9Identify the capabilities of Power BI
- 4.10Describe features of data models in Power BI
- 4.11Identify appropriate visualizations for data
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