Sample chapters

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1.

Active Directory

2.

Clarity

3.

Containerization with Docker

4.

Describe fundamental principles of machine learning on Azure

5.

Designing effective agents

6.

Getting to know Python in Excel

7.

Implement a secure environment

8.

Introducing the filter context and CALCULATE

9.

Manage and maintain devices

10.

My first visual calculation

11.

Setting up GitHub Copilot for your development workflow

  • Feb 25, 2026
12.

Setting up Power BI

  • Feb 25, 2026
13.

This sounds like BASIC, so why doesn't it look familiar?

  • Feb 25, 2026
14.

Creating a basic pivot table

15.

Writing effective prompts for Copilot

16.

Combining Data from Multiple Sources

17.

Explore data and train models

18.

Secure Azure Networks

19.

Data Aggregation

  • By Mark Morowczynski, Rod Trent, Matthew ZorichAug 5, 2024

  • A strength of Kusto Query Language (KQL) is data aggregation. In this sample chapter, you will learn how to turn data into actionable insight and visualize data with graphs and charts. You will perform common statistical analysis on data such as counting totals, distinct counts, and the first and last time an event takes place.

20.

Develop for Azure storage

  • By Santiago Fernandez MunozAug 5, 2024

  • Data storage systems must be designed with geography, latency, and cost efficiency in mind. Microsoft Azure offers cloud-based storage solutions with these points in mind. In this sample chapter, you will learn how to develop solutions that use Cosmos DB and Blob Storage. Exam AZ-204 topics covered include 2.1 and 2.2.

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