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

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 (English Edition)
Publisher finelybook 出版社: Orange Education Pvt. Ltd
Author: Ashish Agarwal (Author)
Publication Date 出版日期: 2024-07-22
Language 语言: English
Print Length 页数: 248 pages
ISBN-10: 8197651140
ISBN-13: 9788197651144


Book Description
By finelybook

Discover the world of data engineering in an on-premises setting versus the Azure cloud


Book Description
By finelybook

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.

Table of Contents
1. Introduction to Data Engineering
2. Understanding SQL and RDBMS Concepts
3. Data Engineering: Azure Versus On-Premises
4. Azure Cloud Concepts
5. Working with Heterogenous Data Sources
6. ETL Concepts
7. Database Design and Modeling
8. Performance Best Practices and Data Security
9. Data Visualization and Application in Real World
10. Data Engineering Certification Guide
Index Amazon page

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