DP-900 Study Guide (Microsoft Azure Data Fundamentals)

In this DP-900 Study Guide, I will share free and paid options, whether books, video training, or links to articles and blog posts.

Watch the DP-900 Study Guide Microsoft Azure Data Fundamentals Video. 👇🏾

DP-900 Microsoft Learning Path

Don’t miss these free, self-paced online resources to help you gain the skills needed to earn your certification. DP-900 online learning paths.

DP-900 Instructor-led training (Microsoft Official Courses)

Students will gain foundational knowledge of core data concepts and related Microsoft Azure data services in this course. 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. In addition, 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 modern data warehousing, real-time analytics, and data visualization. $550 Course DP-900T00: Microsoft Azure Data Fundamentals

DP-900 Video Training

This learning path is designed to help you prepare for the DP-900 Azure Data Fundamentals. $35 monthly subscription A Cloud Guru DP-900 Azure Data Fundamentals

DP-900 Practice Exams

Microsoft Official Practice Tests are self-study tools that prepare candidates for the Microsoft-required exams. $99.00 - $109.00 Microsoft Official Practice Test Fundamentals - Microsoft Official Practice Test

Another practice test and sample questions. Free Examtopics.com Microsoft DP-900 Exam

Audience Profile for the Exam

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

About Exam DP-900: Microsoft Azure Data Fundamentals

Exam DP-900 is required to earn the Azure Data Fundamentals certification. This exam measures your ability to accomplish the following technical tasks: describe core data concepts, explain how to work with relational and non-relational data on Azure, and describe an analytics workload on Azure.

Skills measured

For the complete list of the skills that the exam measures and the level of experience and expertise you’ll need as an exam candidate, check out the Exam DP-900 skills outline.

Objective domains

This section itemizes the topics covered in the Exam Prep session and links to Microsoft documentation so you can review the topics in detail.

• Describe core data concepts (15–20%)

• Describe how to work with relational data on Azure (25–30%)

• Describe how to work with non-relational data on Azure (25–30%)

• Describe an analytics workload on Azure (25–30%)

Describe core data concepts (15–20%)

Describe types of core data workloads

• Overview of data

• Batch versus streaming data

Describe data analytics core concepts

• The data lifecycle

• Extract, transform, and load (ETL) and extract, load, and transform (ELT)

• Data visualization

• Data analytics

Describe how to work with relational data on Azure (25–30%)

Describe relational data workloads

• Characteristics of relational data

• Relational data structures

• Normalization

• Databases in the cloud

• The right platform for a relational workload

Describe relational Azure data services

• SQL Server on Azure Virtual Machines

• Azure SQL Database

• Azure SQL Managed Instance

• PostgreSQL, MySQL, and MariaDB

• Data migration to Azure

Describe how to work with non-relational data on Azure (25–30%)

Describe non-relational data workloads

• Characteristics of non-relational data

• Types of non-relational and NoSQL databases

• Use non-relational data

Describe non-relational data offerings on Azure

• Azure data services

• Azure Table Storage

• Azure Blob Storage

• Azure File storage

• Azure Cosmos DB

• Create an Azure Cosmos DB account: Demo

Identify basic management tasks for non-relational data

• Upload data to Azure Cosmos DB: Demo

• Manage Azure Blob Storage

• Manage Azure File storage

Describe an analytics workload on Azure (25–30%)

Describe analytics workloads

• Transactional workloads

• Transactional versus analytics workloads

• Data warehouse workloads

Describe the components of a modern data warehouse

• Modern data warehousing

• Azure data services for modern data warehousing

Describe data ingestion and processing on Azure

• Common practices for data loading

Describe data visualization in Microsoft Power BI

• Overview of Power BI

• Building blocks of Power BI

• Common chart types

• Use Power BI