Exam DP-900 Microsoft Azure Data Fundamentals

This exam is intended for candidates beginning to work with data in the cloud.

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services, and should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.

This exam is an opportunity to demonstrate your knowledge of core data concepts and related Microsoft Azure data services. As a candidate 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.

• 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%)

• Describe features of structured data

• Describe features of semi-structured

• Describe features of unstructured data

• Describe common formats for data files

• Describe types of databases

• Describe features of transactional workloads

• Describe features of analytical workloads

• Describe responsibilities for database administrators

• Describe responsibilities for data engineers

• Describe responsibilities for data analysts

• Identify features of relational data

• Describe normalization and why it is used

• Identify common structured query language (SQL) statements

• Identify common database objects

• 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 Azure Blob storage

• Describe Azure File storage

• Describe Azure Table storage

• Identify use cases for Azure Cosmos DB

• Describe Azure Cosmos DB APIs

• 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 the difference between batch and streaming data

• Identify Microsoft cloud services for real-time analytics

• Identify capabilities of Power BI

• Describe features of data models in Power BI

• Identify appropriate visualizations for data