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Microsoft Azure Data (DP-900) Exam Questions May – 2025

Name: Microsoft Azure Data (DP-900) Exam Questions May – 2025
Availability: InStock
Rating: 1 (98 reviews)
Author: Zahra Ahmadi Firouz Jaee

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DP-900, Azure Data

 1/5

(98) Ratings

707 students

IT & Software

Created by Zahra Ahmadi Firouz Jaee

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What you'll learn

Explain the differences between relational and non-relational data, and describe different types of data workloads such as transactional and analytical.
Identify and work with Azure services for relational databases such as Azure SQL Database, and understand basic query capabilities.
Learn about non-relational data offerings like Azure Cosmos DB, and when to use them for specific scenarios.
Understand Azure’s data analytics solutions, including Azure Synapse Analytics, Azure Data Lake, and how they support big data and real-time processing.

This course includes:

138 questions on-demand video

0 articles

0 downloadable resources

0 lessons

Full lifetime access

Access on mobile and TV

Certificate of completion

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Course content

Requirements

No prior data or cloud experience is required, but basic familiarity with data concepts and general technology usage is helpful.

Description

Post Views: 142

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 features of structured data
Describe features of semi-structured
Describe features of unstructured data

Identify options for data storage

Describe common formats for data files
Describe types of databases

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 capabilities of Azure storage

Describe Azure Blob storage
Describe Azure File storage
Describe Azure Table storage

Describe 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 consideration 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 capabilities of Power BI
Describe features of data models in Power BI
Identify appropriate visualizations for data

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Who this course is for:

This certification is ideal for beginners, students, or professionals looking to start a career in data or gain foundational knowledge of data services in Microsoft Azure.