DP-900T00-A: Microsoft Azure Data Fundamentals

Prepare to pass the DP-900: Microsoft Azure Data Fundamentals Certification Exam

Course Description

In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization.

Audience Profile

The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.

About this Course

Course Outline

Skills at a glance

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 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