Microsoft Azure Data Fundamentals (DP-900) Cert Prep

Course details

Boost your career as a data science professional by preparing for the Microsoft Azure Data Fundamentals (DP-900) exam. In this cert prep course from Microsoft Press, thought leader and data coach Chris Sorenson unpacks the core concepts and technical skills covered by the exam, including data representation, data storage, common data workloads, roles and responsibilities, relational concepts and services, Azure Cosmos DB, large-scale analytics, and data visualization in Power BI. An ideal fit for new and existing data professionals, this course helps to prepare you to successfully tackle the exam.

Concepts

Introduction

Exam DP-900 Microsoft Azure Data Fundamentals - Introduction

Describe Ways to Represent Data

Module 1 - Describe core data concepts
Learning objectives
Describe features of structured data
Describe features of semi-structured data
Describe features of unstructured data

Identify Options for Data Storage

Learning objectives
Describe common formats for data files
Describe types of databases

Describe Common Data Workloads

Learning objectives
Describe features of transactional workloads
Describe features of analytical workloads

Identify Roles and Responsibilities for Data Workloads

Learning objectives
Describe responsibilities for database administrators
Describe responsibilities for data engineers
Describe responsibilities for data analysts

Describe Relational Concepts

Module 2 - Identify considerations for relational data on Azure
Learning objectives
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

Learning objectives
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 the Capabilities of Azure Storage

Module 3 - Describe considerations for working with non-relational data on Azure
Learning objectives
Describe Azure Blob storage
Describe Azure File storage
Describe Azure Table storage

Describe the Capabilities and Features of Azure Cosmos DB

Learning objectives
Identify use cases for Azure Cosmos DB
Describe Azure Cosmos DB APIs

Describe the Common Elements of Large-Scale Analytics

Module 4 - Describe an analytics workload on Azure
Learning objectives
Describe considerations for data ingestion and processing
Describe options for analytical data stores
Describe Azure services for data warehousing

Describe the Consideration for Real-Time Data Analytics

Learning objectives
Describe the difference between batch and streaming data
Identify Microsoft cloud services for real-time analytics

Describe Data Visualization in Microsoft Power BI

Learning objectives
Identify the capabilities of Power BI
Describe the features of data models in Power BI
Identify appropriate visualizations for data

Summary

Exam DP-900 Microsoft Azure Data Fundamentals - Summary