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

0. Introduction

01 - Exam DP-900 Microsoft Azure Data Fundamentals - Introduction

1. Describe Ways to Represent Data

02 - Module 1 - Describe core data concepts
03 - Learning objectives
04 - Describe features of structured data
05 - Describe features of semi-structured data
06 - Describe features of unstructured data

2. Identify Options for Data Storage

07 - Learning objectives
08 - Describe common formats for data files
09 - Describe types of databases

3. Describe Common Data Workloads

10 - Learning objectives
11 - Describe features of transactional workloads
12 - Describe features of analytical workloads

4. Identify Roles and Responsibilities for Data Workloads

13 - Learning objectives
14 - Describe responsibilities for database administrators
15 - Describe responsibilities for data engineers
16 - Describe responsibilities for data analysts

5. Describe Relational Concepts

17 - Module 2 - Identify considerations for relational data on Azure
18 - Learning objectives
19 - Identify features of relational data
20 - Describe normalization and why it is used
21 - Identify common structured query language (SQL) statements
22 - Identify common database objects

6. Describe Relational Azure Data Services

23 - Learning objectives
24 - Describe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
25 - Identify Azure Database services for open-source database systems

7. Describe the Capabilities of Azure Storage

26 - Module 3 - Describe considerations for working with non-relational data on Azure
27 - Learning objectives
28 - Describe Azure Blob storage
29 - Describe Azure File storage
30 - Describe Azure Table storage

8. Describe the Capabilities and Features of Azure Cosmos DB

31 - Learning objectives
32 - Identify use cases for Azure Cosmos DB
33 - Describe Azure Cosmos DB APIs

9. Describe the Common Elements of Large-Scale Analytics

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

10. Describe the Consideration for Real-Time Data Analytics

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

11. Describe Data Visualization in Microsoft Power BI

42 - Learning objectives
43 - Identify the capabilities of Power BI
44 - Describe the features of data models in Power BI
45 - Identify appropriate visualizations for data

Summary

46 - Exam DP-900 Microsoft Azure Data Fundamentals - Summary