Is DP-900 easier than AZ-900?
DP-900 and AZ-900 are similarly difficult in terms of overall effort, both requiring 2-3 weeks of study for most candidates. DP-900 is more focused, covering data-specific concepts like relational databases, non-relational data, analytics workloads, and Azure data services. Candidates with database or data analyst backgrounds often find DP-900 easier because the concepts are familiar, while general IT professionals may find AZ-900 slightly more accessible.
The DP-900 Microsoft Azure Data Fundamentals certification is Microsoft's entry-level credential for data professionals, validating foundational knowledge of core data concepts and how they are implemented in Azure data services. It covers relational data, non-relational data, analytics, and the Azure services supporting each.
DP-900 is an ideal starting point for data analysts, database administrators, business intelligence professionals, and developers who want to demonstrate cloud data literacy or begin an Azure data career path. The exam costs $99 USD, contains 40-60 questions, and requires a passing score of 700 out of 1000.
Exam Overview
| Detail | Information |
|---|---|
| Exam Code | DP-900 |
| Full Name | Microsoft Azure Data Fundamentals |
| Number of Questions | 40-60 |
| Time Limit | 45 minutes |
| Passing Score | 700/1000 |
| Cost | $99 USD |
| Prerequisites | None |
| Related Paths | DP-203, DP-300, DP-600 |
The exam covers three domains:
- 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%)
"DP-900 is the foundation for anyone entering Azure data roles. Understanding the difference between transactional and analytical workloads, and knowing which Azure service serves each purpose, is the core skill the exam tests. Memorizing service names without understanding why you would choose them leads to wrong answers on scenario questions." -- Microsoft Learn community guidance
Domain 1: Core Data Concepts (25-30%)
Types of Data
Structured data has a defined schema with rows and columns, typically stored in relational databases. Examples: customer records, financial transactions, inventory data.
Semi-structured data has some organizational properties but does not fit neatly into a relational table. Examples: JSON documents, XML files, CSV files with varying fields.
Unstructured data has no predefined schema. Examples: images, videos, audio files, text documents, social media posts.
Transactional vs. Analytical Workloads
| Workload Type | Characteristics | Azure Service |
|---|---|---|
| OLTP (Transactional) | High-frequency read/write, normalized schema, row-based storage | Azure SQL Database, Cosmos DB |
| OLAP (Analytical) | Complex queries, aggregations, historical data, columnar storage | Azure Synapse Analytics, Azure Analysis Services |
| Hybrid | Combined transactional and analytical | Azure Synapse Link, Cosmos DB analytical store |
Data Roles
The exam tests understanding of three key data roles:
- Database Administrator: Manages database infrastructure, performance, backup, recovery, and security
- Data Engineer: Designs and implements data pipelines, ingestion, transformation, and storage
- Data Analyst: Queries and visualizes data to derive business insights
Domain 2: Relational Data on Azure (20-25%)
Azure SQL Family
Microsoft offers multiple relational database services on Azure:
Azure SQL Database: A fully managed PaaS relational database based on the latest stable SQL Server version. Ideal for modern cloud applications requiring automatic patching, backup, and scaling.
Azure SQL Managed Instance: Near-complete SQL Server compatibility in a PaaS form factor, designed for migrating on-premises SQL Server workloads with minimal code changes.
SQL Server on Azure Virtual Machines: Full SQL Server installed on an Azure VM. Maximum compatibility and control, with the customer responsible for OS and SQL Server maintenance.
SQL Fundamentals
DP-900 tests basic SQL knowledge:
- SELECT, FROM, WHERE: Core query structure
- JOIN types: INNER JOIN (matching rows only), LEFT JOIN (all left rows plus matches), RIGHT JOIN, FULL OUTER JOIN
- DDL vs. DML: Data Definition Language (CREATE, ALTER, DROP) vs. Data Manipulation Language (SELECT, INSERT, UPDATE, DELETE)
- Primary and foreign keys: Constraints enforcing referential integrity
Domain 3: Non-Relational Data on Azure (15-20%)
Azure Cosmos DB
Azure Cosmos DB is Microsoft's globally distributed NoSQL database service supporting multiple data models:
- Core (SQL) API: JSON documents queried with SQL-like syntax
- MongoDB API: Wire protocol compatibility with MongoDB drivers
- Cassandra API: Column-family data model
- Gremlin API: Graph data model for connected data
- Table API: Key-value data model compatible with Azure Table Storage
Cosmos DB offers five consistency levels from strongest to weakest: Strong, Bounded Staleness, Session, Consistent Prefix, Eventual.
Azure Storage for Non-Relational Data
- Azure Blob Storage: Object storage for unstructured data (images, videos, documents, backups)
- Azure Table Storage: Simple key-value storage for large volumes of structured, non-relational data (now superseded by Cosmos DB Table API for new workloads)
- Azure Files: Fully managed file shares accessible via SMB and NFS protocols
Domain 4: Analytics Workloads on Azure (25-30%)
Modern Data Warehouse Architecture
A modern data warehouse on Azure typically includes:
- Data ingestion: Azure Data Factory or Azure Synapse pipelines bring data from sources into Azure
- Data storage: Azure Data Lake Storage Gen2 stores raw and transformed data
- Data transformation: Azure Databricks or Synapse Spark pools transform and prepare data
- Analytical database: Azure Synapse dedicated SQL pools provide the serving layer
- Visualization: Microsoft Power BI creates reports and dashboards
Azure Synapse Analytics
Azure Synapse Analytics is an integrated analytics platform combining:
- Dedicated SQL pools: Massively parallel processing (MPP) engine for large-scale data warehousing
- Serverless SQL pool: Ad-hoc querying of data in Azure Data Lake without provisioning infrastructure
- Spark pools: Apache Spark for big data processing and machine learning
- Synapse Pipelines: Data integration and orchestration (equivalent to Azure Data Factory)
- Synapse Link: Real-time analytical processing on operational data without ETL
"Power BI is tested more heavily in DP-900 than most candidates expect. Understanding the difference between Import mode, DirectQuery mode, and Live Connection, and knowing when to use each, is a common exam topic. Candidates who skip the Power BI section often lose 5-10 points." -- Data certification community advice
Power BI Components
| Component | Purpose |
|---|---|
| Power BI Desktop | Authoring tool for building reports and data models |
| Power BI Service | Cloud platform for publishing, sharing, and collaborating |
| Power BI Mobile | Mobile app for consuming reports |
| Power BI Report Server | On-premises report hosting |
| Power BI Embedded | Embedding Power BI visuals in custom applications |
Frequently Asked Questions
What jobs does DP-900 help with? DP-900 demonstrates foundational cloud data literacy and is relevant for data analyst, database administrator, data engineer, and BI developer roles. It is frequently listed as a preferred qualification in Azure data job postings and shows employers that a candidate understands the Azure data services landscape. It is also a stepping stone to role-based data certifications like DP-300 (Database Administrator) and DP-203 (Data Engineer).
How should I study for DP-900? The Microsoft Learn free learning path for DP-900 is comprehensive and well-structured. Complete all four modules on Microsoft Learn, take the knowledge checks at the end of each section, and supplement with at least a few hours in the Azure portal exploring Azure SQL Database, Cosmos DB, and Azure Synapse Analytics. The exam is conceptual, so understanding why each service exists and what problems it solves matters more than memorizing configuration details.
Can DP-900 be taken online at home? Yes, DP-900 can be taken online at home through Pearson VUE's online proctoring service. You will need a reliable internet connection, a webcam, and a quiet, private room. The exam can also be taken at a Pearson VUE testing center. Online and in-person versions are identical in content and scoring.
References
- Microsoft. (2025). Exam DP-900: Microsoft Azure Data Fundamentals. https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-900/
- Microsoft. (2025). Azure Synapse Analytics Documentation. https://learn.microsoft.com/en-us/azure/synapse-analytics/
- Microsoft. (2025). Azure Cosmos DB Documentation. https://learn.microsoft.com/en-us/azure/cosmos-db/
- Microsoft. (2025). Power BI Documentation. https://learn.microsoft.com/en-us/power-bi/
- Gawronski, W. (2024). DP-900 Microsoft Azure Data Fundamentals Study Guide. Packt Publishing.
- Pearson VUE. (2025). Microsoft Certification Exam Information. https://home.pearsonvue.com/microsoft