Ultimate azure data engineering : build robust data engineering systems on azure with SQL, ETL, Data modeling, and Power BI for business insights and crack azure certifications / Ashish Agarwal.

Format:

Book

Author/Creator:

Agarwal, Ashish, author.

Language:

English

Subjects (All):

Microsoft Azure (Computing platform).

SQL (Computer program language).

Physical Description:

1 online resource (191 pages)

Edition:

First edition, English edition.

Place of Publication:

Delhi, India : Orange Education Pvt Ltd, [2024]

Summary:

Embark on a comprehensive journey into Azure data engineering with "Ultimate Azure Data Engineering". Starting with foundational topics like SQL and relational database concepts, you'll progress to comparing data engineering practices in Azure versus on-premises environments. Next, you will dive deep into Azure cloud fundamentals, learning how to effectively manage heterogeneous data sources and implement robust Extract, Transform, Load (ETL) concepts using Azure Data Factory, mastering the orchestration of data workflows and pipeline automation. The book then moves to explore advanced database design strategies and discover best practices for optimizing data performance and ensuring stringent data security measures. You will learn to visualize data insights using Power BI and apply these skills to real-world scenarios. Whether you're aiming to excel in your current role or preparing for Azure data engineering certifications, this book equips you with practical knowledge and hands-on expertise to thrive in the dynamic field of Azure data engineering.

Contents:

Cover Page

Title Page

Copyright Page

Dedication Page

About the Author

About the Technical Reviewer

Acknowledgements

Preface

Errata

Table of Contents

1. Introduction to Data Engineering

Introduction

Structure

Basic Concepts of Data Engineering

Difference Between Data Engineering, Data Analysis, and Data Science

Data Engineering

Data Analyst

Data Scientist

Modern Data Ecosystem

Source Systems, Formats, and Data Types

Source Systems

Source Data Formats

Data Types

Basics of ETL/ELT Concepts

Extract

Transform

Load

Relational and Non-relational Databases

Data Warehouse and Data Marts

Data Lake, Big Data Store, Lakehouse, and Delta Lake Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9788197651144

OCLC:

1450106835