DP-900: Azure Data Fundamentals certification and exam guide
What the certification validates, who it is for, and the relational, non-relational, and analytics data concepts and Azure services it covers.
Aligned with the official Microsoft skills outline updated on July 21, 2026
By João Ricardo Dutra••Complete guide
What is the DP-900 certification?
Microsoft Certified: Azure Data Fundamentals validates foundational knowledge of core data concepts and how Microsoft Azure services support relational, non-relational and analytics workloads. It provides a shared vocabulary for understanding how data is stored, processed and turned into insight in the cloud.
DP-900 is a fundamentals exam. It focuses on recognizing workload patterns, data roles and Azure service capabilities rather than expecting production-level database administration, data engineering or analytics implementation expertise.
Who is it for?
DP-900 is intended for people beginning to work with data in the cloud. It suits students, analysts, developers, database professionals, architects, business stakeholders and career changers who need to distinguish relational, non-relational, transactional and analytical approaches.
Beginners who want a structured introduction to data workloads on Azure.
Professionals who collaborate with database, data engineering or analytics teams.
Candidates considering later role-based certifications in Azure data services.
Decision-makers who need to match a data requirement to an appropriate service family.
Skills measured by the exam
The official Microsoft study guide groups the exam into four domains. The percentages below are approximate and reflect the skills outline updated on July 21, 2026.
DP-900 skills measured
Domain
Weight
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%
Data concepts and Azure services covered
Structured, semi-structured and unstructured data; transactional and analytical workloads; roles such as database administrator, data engineer and data analyst.
Relational concepts including tables, keys, relationships, normalization, SQL and services, plus Azure database services for open-source systems.
Non-relational patterns and services including ,, Azure Table storage and .
Analytics concepts including ingestion, transformation, data warehouses, lakehouses, , and real-time analytics.
Data visualization and reporting concepts with Microsoft .
The goal is to understand the characteristics and typical use cases of these technologies. You should be able to explain why a workload fits a relational database, a document or key-value store, an object store, a lakehouse, a warehouse, a streaming platform or a business intelligence tool.
How to use this learning path
Start with the four official domains and identify unfamiliar concepts. Then use the timed practice tests to alternate assessment and review. After each test, group mistakes by domain and confirm the relevant terminology and current Azure services in Microsoft Learn.
