Book Image

Azure Data Engineer Associate Certification Guide

By : Newton Alex
Book Image

Azure Data Engineer Associate Certification Guide

By: Newton Alex

Overview of this book

Azure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.
Table of Contents (23 chapters)
1
Part 1: Azure Basics
3
Part 2: Data Storage
10
Part 3: Design and Develop Data Processing (25-30%)
15
Part 4: Design and Implement Data Security (10-15%)
17
Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
20
Part 6: Practice Exercises

Implementing logging used by Azure Monitor

Azure Monitor is the service we use to monitor infrastructure, services, and applications. Azure Monitor records two types of data: metrics and logs. Metrics are numerical values that describe an entity or an aspect of a system at different instances of time—for example, the number of gigabytes (GBs) of data stored in a storage account at any point in time, the current number of active pipelines in ADF, and so on. Metrics are stored in time-series databases and can be easily aggregated for alerting, reporting, and auditing purposes.

Logs, on the other hand, are usually text details of what is happening in the system. Unlike metrics, which are recorded at regular intervals, logs are usually event-driven. For example, a user logging in to a system, a web app receiving a REpresentational State Transfer (REST) request, and triggering a pipeline in ADF could all generate logs.

Since Azure Monitor is an independent service, it can aggregate...