Practice Exams | Microsoft Azure DP-900 Data Fundamentals

About Practice Exams | Microsoft Azure DP-900 Data Fundamentals

_In order to set realistic expectations, please note: These questions are NOT official questions that you will find on the official exam. These questions DO cover all the material outlined in the knowledge sections below. Many of the questions are based on fictitious scenarios which have questions posed within them._

_The official knowledge requirements for the exam are reviewed routinely to ensure that the content has the latest requirements incorporated in the practice questions. Updates to content are often made without prior notification and are subject to change at any time._

Each question has a detailed explanation and links to reference materials to support the answers which ensures accuracy of the problem solutions.

The questions will be shuffled each time you repeat the tests so you will need to know why an answer is correct, not just that the correct answer was item "B" last time you went through the test. _NOTE: This course should not be your only study material to prepare for the official exam. These practice tests are meant to supplement topic study material._

Should you encounter content which needs attention, please send a message with a screenshot of the content that needs attention and I will be reviewed promptly. Providing the test and question number do not identify questions as the questions rotate each time they are run. The question numbers are different for everyone.

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. 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 (25–30%) Describe common elements of large-scale analytics

Describe considerations for data ingestion and processing

Describe options for analytical data stores

Describe Microsoft cloud services for large-scale analytics, including Azure Databricks and Microsoft Fabric 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