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

Designing for incremental loading

Incremental loading or delta loading refers to the process of loading smaller increments of data into a storage solution—for example, we could have daily data that is being loaded into a data lake or hourly data flowing into an extract, transform, load (ETL) pipeline, and so on. During data-ingestion scenarios, it is very common to do a bulk upload followed by scheduled incremental loads.

Azure has a very versatile service called Azure Data Factory (ADF) which can help with incremental loading. Since this is the first time we are using ADF in this book, let's learn a little more about it now as the information will come in handy in future chapters.

ADF is a managed cloud service that can be used to coordinate and orchestrate complex cloud- or hybrid- (on-premises)-based pipelines. ADF provides the ability to build ETL and extract, load, transform (ELT) pipelines. With ADF, you can do the following:

  • Ingest data from a wide...