Microsoft Azure Data Fundamentals [DP-900] Exam Guide (2026)
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Microsoft Azure Data Fundamentals (DP-900) - Complete Exam Guide
Introduction: Why Get Azure Data Fundamentals Certified?
The Microsoft Azure Data Fundamentals (DP-900) certification validates your foundational knowledge of core data concepts and Azure data services.
This certification is ideal for business stakeholders, aspiring data professionals, and anyone working with data in the cloud. You'll learn about relational and non-relational databases, data analytics, and data processing on Azure.
This certification demonstrates that you understand different data types, when to use various Azure data services, and how to work with both transactional and analytical workloads. Whether you're a data analyst, business intelligence professional, or database administrator starting your cloud journey, this certification validates your foundational data knowledge.
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Exam Overview: What You're Getting Into
Exam Details at a Glance
- Exam Code: DP-900
- Duration: 60 minutes
- Number of Questions: 40-60 questions
- Question Format: Multiple choice, multiple response, true/false, matching, drag-and-drop
- Passing Score: 700 out of 1000 (approximately 70%)
- Cost: $99 USD (or local currency equivalent)
- Validity: Does not expire
- Delivery Method: Pearson VUE testing centers or online proctored exam
- Prerequisites: None—foundational certification
- Recommended Knowledge: Basic understanding of data concepts
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What Makes This Exam Different
This exam tests your understanding of data concepts and Azure services, not deep technical implementation. You need to understand relational vs. non-relational data, OLTP vs. OLAP workloads, and when to use different Azure data services but you don't need to write complex SQL queries or design advanced data architectures.
The exam emphasizes matching business requirements to appropriate Azure services and understanding trade-offs between different data storage and processing options.
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Exam Domains: Breaking Down What's Tested
Domain 1: Describe Core Data Concepts (25-30% of exam)
Key Topics:
- Data Types:
- Structured Data: Organized in tables with defined schema (SQL databases)
- Semi-Structured Data: Has some structure but flexible (JSON, XML)
- Unstructured Data: No predefined structure (images, videos, documents)
- Data Storage Options: Files, databases, data lakes
- Data Workloads:
- OLTP (Online Transaction Processing): Real-time transactions, INSERT/UPDATE/DELETE operations
- OLAP (Online Analytical Processing): Historical data analysis, complex queries, reporting
- Data Professional Roles:
- Database Administrator (DBA): Manages databases, backups, security, performance
- Data Engineer: Builds data pipelines, ETL processes, data infrastructure
- Data Analyst: Analyzes data, creates visualizations and reports
Exam Question Style:
"A retail company needs to track real-time inventory transactions across multiple stores. Hundreds of updates occur per second. Which type of workload is this?"
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Domain 2: Identify Considerations for Relational Data on Azure (20-25% of exam)
Key Topics:
- Relational Concepts:
- Tables, rows, columns, primary keys, foreign keys
- Normalization (reducing data redundancy)
- SQL statements (SELECT, INSERT, UPDATE, DELETE, CREATE, JOIN)
- Database objects (tables, views, stored procedures, indexes)
- Azure SQL Family:
- Azure SQL Database: Fully managed PaaS database, automatic backups, scaling
- Azure SQL Managed Instance: Near 100% compatibility with SQL Server, lift-and-shift
- SQL Server on Azure VMs: Full control, IaaS approach
- Open-Source Databases:
- Azure Database for MySQL
- Azure Database for PostgreSQL
- Azure Database for MariaDB
Exam Question Style:
"A company wants to migrate their on-premises SQL Server database to Azure with minimal code changes. They need maximum SQL Server compatibility. Which Azure service should they choose?"
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Domain 3: Describe Considerations for Working with Non-Relational Data on Azure (15-20% of exam)
Key Topics:
- Azure Storage Services:
- Azure Blob Storage: Store massive amounts of unstructured data (images, videos, logs)
- Azure File Storage: Cloud file shares accessible via SMB protocol
- Azure Table Storage: NoSQL key-value store for simple data
- Azure Cosmos DB:
- Globally distributed, multi-model NoSQL database
- Multiple APIs: Core (SQL), MongoDB, Cassandra, Gremlin, Table
- Automatic indexing and multi-region replication
- Ideal for globally distributed applications with low latency requirements
Exam Question Style:
"A social media application needs to store user posts, comments, and relationships with guaranteed sub-10ms latency for users worldwide. Which Azure service is most appropriate?"
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Domain 4: Describe an Analytics Workload on Azure (25-30% of exam)
Key Topics:
- Data Ingestion and Processing:
- Batch Processing: Processing large volumes of data at scheduled intervals
- Real-Time/Streaming Processing: Processing data as it arrives
- ETL (Extract, Transform, Load): Moving and transforming data
- Azure Analytics Services:
- Azure Synapse Analytics: Enterprise data warehousing and big data analytics
- Azure Databricks: Apache Spark-based analytics platform
- Azure Data Factory: ETL and data integration service
- Azure Stream Analytics: Real-time stream processing
- Azure Data Lake Storage: Scalable data lake for analytics
- Microsoft Fabric: Unified analytics platform
- Power BI:
- Data visualization and business intelligence
- Create reports and dashboards
- Share insights across organization
- Connect to multiple data sources
Exam Question Style:
"A company needs to process sensor data from IoT devices in real-time and trigger alerts when values exceed thresholds. Which Azure service should they use?"
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The Must-Know Services: Your Priority List
Critical Services (Master These)
Relational Databases:
- Azure SQL Database: Managed SQL database (PaaS)
- Azure SQL Managed Instance: SQL Server compatibility
- SQL Server on Azure VMs: Full control (IaaS)
- Azure Database for MySQL/PostgreSQL/MariaDB: Open-source options
Non-Relational Storage:
- Azure Blob Storage: Object storage (hot, cool, archive tiers)
- Azure File Storage: File shares in the cloud
- Azure Table Storage: NoSQL key-value storage
- Azure Cosmos DB: Globally distributed NoSQL database
Analytics:
- Azure Synapse Analytics: Data warehousing and analytics
- Azure Databricks: Spark-based analytics
- Azure Data Factory: ETL and data pipelines
- Azure Stream Analytics: Real-time stream processing
- Azure Data Lake Storage Gen2: Scalable data lake
- Power BI: Business intelligence and visualization
High-Frequency Exam Topics
- OLTP vs. OLAP - Transaction processing vs. analytics
- Structured vs. Semi-Structured vs. Unstructured Data - Know the differences
- Azure SQL Family - Database vs. Managed Instance vs. VM
- Cosmos DB APIs - Core (SQL), MongoDB, Cassandra, etc.
- Blob Storage Tiers - Hot, cool, archive for cost optimization
- Batch vs. Streaming - When to use each processing approach
- Data Professional Roles - DBA vs. Data Engineer vs. Data Analyst
- Normalization - Reducing data redundancy in relational databases
- Power BI Capabilities - Visualization and reporting features
- Data Ingestion - Azure Data Factory and data pipelines
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Study Strategy: Your Path to Success
Phase 1: Core Data Concepts (1-2 Weeks)
- Data types (structured, semi-structured, unstructured)
- OLTP vs. OLAP workloads
- Data professional roles
Phase 2: Relational Data on Azure (1-2 Weeks)
- Relational database concepts
- Azure SQL family differences
- Open-source database options
Phase 3: Non-Relational Data on Azure (1-2 Weeks)
- Azure Storage services
- Azure Cosmos DB capabilities and APIs
- When to use non-relational vs. relational
Phase 4: Analytics Workloads (2 Weeks)
- Batch vs. streaming processing
- Azure analytics services
- Power BI capabilities
- Data ingestion and ETL
Phase 5: Practice and Refinement (1-2 Weeks)
- Take practice exams
- Analyze weak domains
- Review and improve
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Exam Day Strategy: Maximizing Your Performance
During the Exam
- Identify Data Types: Determine if the scenario involves structured, semi-structured, or unstructured data
- Match Workloads: Recognize OLTP vs. OLAP requirements
- Service Selection: Choose the most appropriate Azure service for the scenario
- Consider Trade-Offs: Think about cost, performance, and management overhead
- Time Management: 60 minutes is adequate—don't rush
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Common Traps to Avoid
- Confusing Azure SQL Options: Know when to use Database vs. Managed Instance vs. VM
- Blob vs. File Storage: Understand the differences and use cases
- OLTP vs. OLAP: Don't confuse transaction processing with analytics
- Cosmos DB APIs: Know which API for which scenario
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Resources for Success
Official Microsoft Resources
- Microsoft Learn: Free training modules for DP-900
- Azure Free Account: Try Azure data services hands-on
- Azure Documentation: Service documentation and guides
CloudFluently Course Package Includes
- Comprehensive Study Notes: Clear explanations of data concepts and Azure services
- 180 Practice Questions: Three full-length exams with explanations
- Quick Reference Cheatsheets: Service comparisons, decision trees
- Flashcards: Key concepts for active recall
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After You Pass: What's Next?
Career Advancement
- Azure Database Administrator Associate - Specialize in database management
- Azure Data Engineer Associate - Build data pipelines and infrastructure
- Azure Data Analyst Associate - Focus on analytics and Power BI
- Azure Data Scientist Associate - Machine learning and data science
Continued Learning
- Build data projects using Azure services
- Learn Power BI for advanced visualizations
- Explore data engineering with Azure Data Factory
- Master SQL and data modeling
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Final Thoughts: You're Ready for This
The Azure Data Fundamentals certification validates your understanding of core data concepts and Azure data services. Focus on understanding data types, workload characteristics, and when to use different Azure services. Match business requirements to appropriate services and understand trade-offs.
The combination of study notes, practice exams, and hands-on exploration in this package gives you everything you need to pass confidently.
Good luck, future Microsoft Certified: Azure Data Fundamentals! 📊☁️
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