Microsoft · DP-900
Demonstrate foundational knowledge of core data concepts related to Microsoft Azure data services, including relational and non-relational data, analytics workloads, and Azure data services.
Practice Questions
381
≈ 7 practice exams
Duration
45 minutes
Passing Score
700/1000
Difficulty
FoundationalLast Updated
Jan 2025
Use this DP-900 practice exam to prepare for Microsoft Certified: Azure Data Fundamentals (DP-900) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 381 questions for Microsoft DP-900, so you can review the exam steadily instead of relying on one long cram session.
As you practice, pay extra attention to recurring topics such as Core data concepts, Relational data on Azure, Non-relational data on Azure, and Analytics workload on Azure. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.
The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.
The Microsoft Certified: Azure Data Fundamentals (DP-900) is a foundational-level certification that validates a candidate's knowledge of core data concepts and Microsoft Azure data services. It covers how data is represented and stored — including structured, semi-structured, and unstructured formats — and introduces the key differences between relational and non-relational databases. The exam also addresses transactional and analytical data workloads, equipping candidates with a conceptual foundation for working with cloud data.
The certification spans four primary knowledge areas: core data concepts, relational data on Azure (including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure VMs), non-relational data on Azure (Azure Blob, File, Table storage, and Azure Cosmos DB), and analytics workloads (Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, and Power BI). Last updated on October 31, 2025, the exam reflects current Azure services including Microsoft Fabric and its integration within large-scale analytics pipelines. It is a single-exam certification — passing Exam DP-900 earns the full Microsoft Certified: Azure Data Fundamentals credential.
This certification is designed for candidates who are beginning to work with data in the cloud and want to establish a foundational understanding of Azure data services. It is well-suited for students, career changers moving into data-related roles, business analysts, IT generalists, and junior data professionals who need a conceptual grounding before pursuing more advanced Azure certifications.
Common job roles that benefit from this certification include data analyst, database administrator, data engineer, cloud administrator, and business intelligence developer — all at an entry or transitional career stage. DP-900 also serves as an optional stepping stone toward more advanced credentials such as the Azure Database Administrator Associate (DP-300) and the Azure Data Engineer Associate (DP-203), though it is not a formal prerequisite for either.
There are no mandatory prerequisites for the DP-900 exam. Microsoft does not require any prior certification or formal educational background to register and sit for the exam. However, candidates are expected to have basic familiarity with the concepts of relational and non-relational data, and an understanding of different data workload types such as transactional and analytical processing.
Microsoft recommends completing the official self-paced learning paths available on Microsoft Learn or the instructor-led course DP-900T00-A before taking the exam. Candidates with some background in databases, SQL, or general cloud computing concepts will find the material more accessible, but no hands-on Azure experience is strictly required for this foundational-level exam.
The DP-900 exam is administered through Pearson VUE (for general candidates) or Certiport (for students and educators). Candidates have 45 minutes to complete the assessment. The exam may include interactive components in addition to standard multiple-choice and select-all-that-apply question types. The exam is proctored and can be taken online or at a testing center.
Scoring is on a scale of 1–1000, and a score of 700 or higher is required to pass. The exam does not publish an exact fixed number of questions, as question counts can vary. If the exam is not available in a candidate's preferred language, an additional 30 minutes is granted. Available languages include English, Japanese, Chinese (Simplified and Traditional), Korean, French, German, Spanish, Portuguese (Brazil), Russian, Indonesian, Arabic (Saudi Arabia), and Italian. If a candidate fails, they may retake the exam 24 hours after the first attempt.
The DP-900 certification adds a Microsoft Certified credential to a candidate's professional profile, signaling foundational cloud data competency to employers in a market where Azure is used by more than half of Fortune 500 companies. While the certification itself is entry-level and does not command a salary premium on its own, it serves as a documented entry point into the Azure data career path. Professionals who continue to DP-300 (Azure Database Administrator Associate) or DP-203 (Azure Data Engineer Associate) can target roles with US average salaries in the range of $129,000–$132,000 annually.
The certification is particularly valuable for career changers and early-stage data professionals seeking to validate foundational knowledge before specializing. It supports transitions into roles such as junior data analyst, data technician, cloud administrator with data responsibilities, and business intelligence developer. Because it is a globally recognized Microsoft credential, it retains relevance across industries and geographies, and its low barrier to entry (no prerequisites, low cost, short exam) makes it an efficient first credential in a broader Azure data certification strategy.
5 sample questions with answers and explanations. The full bank has 381 questions, enough for 7 full-length practice exams.
Preview — answers shown1. An enterprise architect at 'Global Data Solutions' is provisioning a new Azure Data Lake Storage Gen2 account to store analytics data. They have already created an Azure Resource Group to contain all related resources. To organize the data for different projects, they need to create the correct hierarchical structure inside the storage account. What is the correct sequence of components, from largest to smallest, inside the Resource Group?
Explanation
The correct hierarchy within an Azure Resource Group for Azure Data Lake Storage Gen2 is: an Azure Storage account, which acts as the top-level object for the storage itself. Inside the storage account, you create a Container, which serves as the primary namespace or root directory for your data lake. Finally, within the container, you organize your data using Folders and Files. File shares are associated with Azure Files service, not Data Lake Storage.
2. A healthcare application company, 'MedTech Solutions', uses MariaDB for their patient management system and wants to move to Azure while keeping their existing database engine. They need automatic backups, patching, and monitoring without managing the underlying infrastructure. Which Azure service should they choose?
Explanation
Azure Database for MariaDB provides fully managed MariaDB hosting with automatic backups, patching, and monitoring. This PaaS service allows the company to keep their existing MariaDB-based applications while gaining the benefits of a managed service without infrastructure management overhead. MariaDB on VMs would require manual management. SQL Managed Instance is for SQL Server. Cosmos DB is a different NoSQL database technology.
3. A junior database developer is designing a system for a university. In their first draft, for every course a student enrolls in, they store the student's full name, date of birth, and home address directly in the enrollment record. A senior architect advises them to normalize the database by creating a separate 'Students' table to store student details and only reference the StudentID in the 'Enrollments' table. What is the primary reason for this normalization process?
Explanation
The primary goal of normalization is to reduce data redundancy. By storing the student's address in only one place (the 'Students' table), you avoid repeating it for every single course they take. This directly improves data integrity, because if a student moves, you only need to update their address in one single record, eliminating the risk of having conflicting or outdated addresses in your database.
4. A satellite constellation operator, 'SpaceData Networks', manages thousands of satellites generating continuous Earth observation data. The ground stations have limited communication windows with each satellite, and data must be prioritized based on mission importance and storage constraints. Which data management strategy optimizes this space-based data collection?
Explanation
Edge computing with intelligent data filtering is most suitable for satellite data management. Each satellite can run edge computing algorithms to analyze data locally, filter out unimportant information, and prioritize critical observations for transmission during limited communication windows. This reduces bandwidth requirements while ensuring important data reaches ground stations. Hierarchical storage management works on ground but doesn't address satellite transmission constraints. Compressed sensing helps with storage but doesn't prioritize data. Priority queuing manages transmission but doesn't reduce data volume through intelligent filtering.
5. A manufacturing company, 'ProductionMetrics Inc', collects sensor data from factory equipment throughout the day and analyzes it overnight to generate daily production reports. The analysis involves complex calculations on the entire day's data and doesn't need to be real-time. Which data processing approach is most suitable?
Explanation
Batch data processing is most suitable for daily production reports that analyze an entire day's worth of sensor data. Batch processing is efficient for large volumes of data that can be processed together, doesn't require real-time results, and is cost-effective for complex calculations that can run during off-peak hours. Real-time streaming would be unnecessarily expensive for non-urgent reports. Interactive querying is for ad-hoc analysis. Manual processing isn't feasible for large sensor datasets.
Microsoft Certified: Azure AI Fundamentals (AI-900)
AI-900 · 464 questions
Microsoft Azure AI Fundamentals (AI-901)
AI-901 · 600 questions
Microsoft Certified: Azure Cosmos DB Developer Specialty (DP-420)
DP-420 · 677 questions
Microsoft Certified: Azure Data Scientist Associate (DP-100)
DP-100 · 987 questions
Microsoft Certified: Azure Database Administrator Associate (DP-300)
DP-300 · 389 questions
Microsoft Certified: Azure Developer Associate (AZ-204)
AZ-204 · 640 questions
$17.99
One-time access to this exam