Updated: Oct 12, 2026
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure Data Fundamentals |
| Exam Number: | DP-900 |
| Exam Format: | Multiple select, Drag and drop, Case-based questions, Multiple choice |
| Real Exam Qty: | 40-60 |
| Exam Price: | 99 USD (varies by country/region) |
| Related Certifications: | Microsoft Certified: Azure Database Administrator Associate Microsoft Certified: Azure Data Engineer Associate Microsoft Certified: Azure AI Engineer Associate |
| Available Languages: | Chinese (Simplified), German, English, French, Italian, Korean, Spanish, Japanese, Portuguese (Brazil) |
| Certificate Validity Period: | Does not expire (Fundamentals certification currently does not require renewal) |
| Exam Duration: | 45-60 |
| Passing Score: | 700 (out of 1000) |
| Recommended Training: | Microsoft Learn DP-900 Learning Path Azure Data Fundamentals Course |
| Exam Registration: | Pearson VUE Registration Portal Microsoft Learn Certification Page |
| Sample Questions: | Microsoft DP-900 Sample Questions |
| Exam Way: | Online proctored exam via Pearson VUE or in-person test center |
| Pre Condition: | No prerequisites required; intended for beginners in data concepts and Azure services. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-data-fundamentals/ |
Explain the Concepts of Core Data: 15-20%
Microsoft Azure Data Fundamentals is an exam that identifies individuals who have the knowledge to work with Azure data storage features. Building on previous core principles of data management, Azure Data Fundamentals exam is designed to evaluate the ability of the candidate. Money designed to assess the skills level for both professionals and students. Determine the type of skills required for a particular situation, for example, a cloud administrator or a data analyst. Gen candidate will have to know the fundamentals of Data Management to work with Azure data storage, create tools to manage data, locate, protect and process it. Relevant topics in a data management environment, a certified candidate should understand. Dml, Db, protection tools through recovery, recovery strategies, documentation data management policies, data loss prevention tools to backup and recovery for backup recovery.
This domain of the DP-900 exam measures one’s knowledge of analytics workloads, data processing, and ingestion on Azure, as well as the elements of modern data warehouses. The candidates will also be tested on their understanding of data visualization within Microsoft Power BI. This involves describing the specific role of dashboards, paginated reporting, interactive reports, and workflows in Power BI.
The questions from this section will evaluate the understanding of the candidates in non-relational data workloads as well as non-relational data contributions on Azure. They must be able to explain Azure File storage, Azure Cosmos DB APIs, Azure Blob Storage, and Azure Table storage. They should also be able to identify the foundational management tasks for non-relational data.
Within this subject area, the students should be able to explain different categories of core data workloads that are available. To answer questions from this subtopic, the examinees should be able to explain batch data and streaming data. They should also know the attributes of relational data and core differences between streaming and batch data. It also covers their skills in core concepts of data analytics. This requires an understanding of data visualization, basic chart types, analytics techniques, data processing concepts, as well as ETL & ELT processing.
The test takers will be required to have the ability to describe some concepts in this topic, including relational data workloads and relational Azure data services. They will also need to know how to identify the basic management functions for relational data. Additionally, they need to possess a good understanding of how to use the SQL language to describe the query methods for data.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics Workloads in Azure | 25-30% | - Azure analytics services
- Data visualization and reporting - Data analytics concepts |
| Topic 2: Non-Relational Data in Azure | 15-20% | - Data processing options for non-relational data - Azure storage services
|
| Topic 3: Core Data Concepts | 25-30% | - Relational vs non-relational data - Data analytics workloads overview - Types of core data workloads - Roles and responsibilities in data work |
| Topic 4: Relational Data in Azure | 20-25% | - Querying relational data - Azure relational data services
|
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