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FundamentalsDP-900

Microsoft Azure Data Fundamentals

Demonstrate foundational knowledge of core data concepts and Azure data services — covering relational, non-relational, and analytics workloads.

Study Hours
10h
Prep Time
~4 weeks
Avg. Pass Rate
81%

Topics Covered

Relational Data
Non-Relational Data
Analytics Workloads
Azure Databases

Skills measured

Official study guide

Microsoft's own objectives, in the order the exam presents them. Each area links to its section on Microsoft Learn. Checked 2026-10-26.

  1. Describe core data concepts25–30%
    This area on Microsoft Learn

    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
  2. Identify considerations for relational data on Azure20–25%
    This area on Microsoft Learn

    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
  3. Describe considerations for working with non-relational data on Azure15–20%
    This area on Microsoft Learn

    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
  4. Describe an analytics workload25–30%
    This area on Microsoft Learn

    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

Microsoft Learn Modules

1Explore core data concepts2Explore relational data in Azure3Explore non-relational data in Azure4Explore analytics in Azure

What to Study Next

DP-300
Administering Azure SQL Solutions
DP-420
Designing and Implementing Cloud-Native Applications Using Azure Cosmos DB
DP-700
Implementing Data Engineering Solutions Using Fabric