This exam is an opportunity to demonstrate your knowledge of core data concepts and related Microsoft Azure data services. As a candidates for this exam, you should have familiarity with Exam DP-900’s self-paced or instructor-led learning material.
This exam is intended for you, if you’re a candidate beginning to work with data in the cloud.
You should be familiar with:
- The concepts of relational and non-relational data.
- Different types of data workloads such as transactional or analytical.
You can use Azure Data Fundamentals to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it is not a prerequisite for any of them.
Microsoft Azure Data Fundamentals Exam Summary:
| Exam Name | Microsoft Certified - Azure Data Fundamentals |
| Exam Code | DP-900 |
| Exam Price | $99 (USD) |
| Exam Price | 60 mins |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | DP-900T00-A: Microsoft Azure Data Fundamentals |
| Sample Questions | Microsoft Azure Data Fundamentals Sample Questions |
| Practice Exam | Microsoft DP-900 Certification Practice Exam |
Microsoft DP-900 Exam Syllabus Topics:
| Topic | Details |
| Describe core data concepts (25-30%) | |
| Describe ways to represent data | - Describe features of structured data - Describe features of semi-structured - Describe features of unstructured data |
| Identify options for data storage | - Describe common formats for data files - Describe types of databases |
| Describe common data workloads | - Describe features of transactional workloads - Describe features of analytical workloads |
| Identify roles and responsibilities for data workloads | - Describe responsibilities for database administrators - Describe responsibilities for data engineers - Describe responsibilities for data analysts |
| Identify considerations for relational data on Azure (20-25%) | |
| Describe relational concepts | - Identify features of relational data - Describe normalization and why it is used - Identify common structured query language (SQL) statements - Identify common database objects |
| Describe relational Azure data services | - Describe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines - Identify Azure database services for open-source database systems |
| Describe considerations for working with non-relational data on Azure (15-20%) | |
| Describe capabilities of Azure storage | - Describe Azure Blob storage - Describe Azure File storage - Describe Azure Table storage |
| Describe capabilities and features of Azure Cosmos DB | - Identify use cases for Azure Cosmos DB - Describe Azure Cosmos DB APIs |
| Describe an analytics workload on Azure (25-30%) | |
| Describe common elements of large-scale analytics | - Describe considerations for data ingestion and processing - Describe options for analytical data stores - Describe Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, Azure HDInsight, and Azure Data Factory |
| Describe consideration for real-time data analytics | - Describe the difference between batch and streaming data - Identify Microsoft cloud services for real-time analytics |
| Describe data visualization in Microsoft Power BI | - Identify capabilities of Power BI - Describe features of data models in Power BI - Identify appropriate visualizations for data |
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