[100% Off] Dp-900 Microsoft Azure Data Fundamentals Qa Tests 2026
Prepare for your DP-900 Microsoft Azure Data Fundamentals Exam Test (Verified QA Updated)
What you’ll learn
- Preparation for DP-900 Microsoft Azure Data Fundamentals,Test your skill before appearing the real exam,Get DP-900 Microsoft Azure Data Fundamentals Questions Answers,Improve skill for Microsoft Certified Azure Data Fundamentals
Requirements
- Azure Data Skill
Description
Are you ready to prepare for the DP-900 Microsoft Azure Data Fundamentals Exam 2026 ?
This exam is an opportunity to demonstrate your knowledge of core data concepts and related Microsoft Azure data services. As a candidate for this exam, you should have familiarity with Exam DP-900’s self-paced or instructor-led learning material.
This exam is intended for you, if you’re a candidate beginning to work with data in the cloud.
You should be familiar with:
The concepts of relational and non-relational data.
Different types of data workloads such as transactional or analytical.
You can use Azure Data Fundamentals to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it is not a prerequisite for any of them.
Skills at a glance
Describe core data concepts (25–30%)
Identify considerations for relational data on Azure (20–25%)
Describe considerations for working with non-relational data on Azure (15–20%)
Describe an analytics workload on Azure (25–30%)
Describe core data concepts (25–30%)
Describe ways to represent data
Describe the features of structured data
Describe the features of semi-structured data
Describe the features of unstructured data
Identify options for data storage
Describe common formats for data files
Describe features of common data stores including databases
Identify Azure datastores for common use cases
Describe common data workloads
Describe features of transactional workloads
Describe features of analytical workloads
Identify roles and responsibilities for data workloads
Describe responsibilities for database administrators
Describe responsibilities for data engineers
Describe responsibilities for data analysts
Identify considerations for relational data on Azure (20–25%)
Describe relational concepts
Identify features of relational data
Describe normalization and why it is used
Identify common structured query language (SQL) statements
Identify common database objects
Describe relational Azure data services
Describe the Azure SQL family of products, including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
Identify Azure database services for open-source database systems
Describe considerations for working with non-relational data on Azure (15–20%)
Describe the capabilities of Azure storage
Describe features of Azure Blob storage
Describe features of Azure Files
Describe features of Azure Table storage
Describe the capabilities and features of Azure Cosmos DB
Identify use cases for Azure Cosmos DB
Describe Azure Cosmos DB APIs
Describe an analytics workload (25–30%)
Describe common elements of large-scale analytics
Describe considerations for data ingestion and processing
Describe options for analytical data stores
Describe Microsoft cloud services for large-scale analytics, including Azure Databricks and Microsoft Fabric
Describe considerations for real-time data analytics
Describe the difference between batch and streaming data
Identify Microsoft cloud services for real-time analytics
Describe data visualization in Microsoft Power BI
Identify the capabilities of Power BI
Describe features of data models in Power BI
Identify appropriate visualizations for data
