The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data

The Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data.
This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics.
By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.

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The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data

The Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data.
This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics.
By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.

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The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data

The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data

The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data
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The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data

The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data

Overview

The Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data.
This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics.
By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.

Product Details

ISBN-13: 9781837634774
Publisher: Packt Publishing
Publication date: 03/29/2024
Sold by: Barnes & Noble
Format: eBook
Pages: 490
File size: 8 MB

About the Author

Pierre-Yves Bonnefoy is a versatile Data & Cloud Architect boasting over 20 years of experience across diverse technical and functional domains. With an extensive background in software development, systems and networks, data analytics, and data science, Pierre-Yves offers a comprehensive view of information systems. As the CEO of Olexya and CTO of Africa4Data, he dedicates his efforts to delivering cutting-edge solutions for clients and promoting data-driven decision making. As an active board member of French Tech Le Mans, Pierre-Yves enthusiastically supports the local tech ecosystem, fostering entrepreneurship and innovation while sharing his expertise with the next generation of tech leaders.
Emeric Chaize, with over 16 years of experience in data management and cloud technology, demonstrates profound knowledge of data platforms and their architecture, further exemplified by his role as President of Olexya, a Data Architecture company. His background in Computer Science and Engineering, combined with hands-on experience, has honed his skills in understanding complex data architectures and implementing efficient data integration solutions. His work at various small and large companies has demonstrated his proficiency in implementing cloud-based data platforms and overseeing data-driven projects, making him highly suited for roles involving data platforms and data integration challenges.
Raphaël Mansuy is a seasoned technology executive and entrepreneur with over 25 years of experience in software development, digital transformation, and AI-driven solutions. As a founder of several companies, he has demonstrated success in designing and implementing mission-critical solutions for global enterprises, creating innovative technologies, and fostering business growth. Raphaël is highly skilled in AI, data engineering, DevOps, and cloud-native development, offering consultancy services to Fortune 500 companies and startups alike. He is passionate about enabling businesses to thrive using cutting-edge technologies and insights.
Mehdi TAZI is a Data & Cloud Architect with over 12 years of experience and the CEO of an IT consulting & Investment companies. He is specialized in distributed information systems and Data Architecture. Mehdi designs Information Systems Architectures that answer customers' needs by setting up technical, functional, and organizational solutions, as well as designing and coding in programming languages such as Java, Scala, or Python.

Table of Contents

Table of Contents
  1. Introduction to our data integration journey
  2. Introducing Data Integration
  3. Architecture and History of Data Integration
  4. Data Sources and Types
  5. Columnar Data Formats and comparisons
  6. Data Storage Technologies and Architectures
  7. Data Ingestion and Storage Strategies
  8. Data Integration Techniques
  9. Data Transformation and Processing
  10. Transformation patterns, cleansing and normalization
  11. Data Exposition and APIs
  12. Data Preparation and Analysis
  13. Workflow Management, Monitoring, and Data Quality
  14. Lineage, Governance, and Compliance
  15. Various Architecture Use Cases
  16. Prospects and Challenges
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