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The Definitive Guide to Data Integration

You're reading from The Definitive Guide to Data Integration Unlock the power of data integration to efficiently manage, transform, and analyze data

Product type Paperback

Published in Mar 2024

Publisher Packt

ISBN-13 9781837631919

Length 490 pages

Edition 1st Edition

Concepts

Data Engineering

Authors (4):

Raphaël MANSUY

Pierre-Yves BONNEFOY

Emeric CHAIZE

Mehdi TAZI

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Table of Contents (19) Chapters

Preface

1. Chapter 1: Introduction to Our Data Integration Journey

2. Chapter 2: Introducing Data Integration FREE CHAPTER

3. Chapter 3: Architecture and History of Data Integration

4. Chapter 4: Data Sources and Types

5. Chapter 5: Columnar Data Formats and Comparisons

6. Chapter 6: Data Storage Technologies and Architectures

7. Chapter 7: Data Ingestion and Storage Strategies

8. Chapter 8: Data Integration Techniques

9. Chapter 9: Data Transformation and Processing

10. Chapter 10: Transformation Patterns, Cleansing, and Normalization

11. Chapter 11: Data Exposition and APIs

12. Chapter 12: Data Preparation and Analysis

13. Chapter 13: Workflow Management, Monitoring, and Data Quality

14. Chapter 14: Lineage, Governance, and Compliance

15. Chapter 15: Various Architecture Use Cases

16. Chapter 16: Prospects and Challenges

17. Index

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18. Other Books You May Enjoy

Massively parallel processing

Massively parallel processing (MPP) engines and databases represent a distinct type of data processing system, specifically designed to execute complex analytical queries over large data volumes. They employ a divide-and-conquer methodology, enabling speedy data processing by distributing data across multiple nodes for simultaneous processing.

At their core, MPP engines harness the power of parallelism. Each node operates independently of the others, working on its portion of the data. Every node has storage, memory, and processing units, ensuring that there is no bottleneck in terms of resources. This distribution of data and computation is what grants MPP engines and databases their scalability and efficiency. As data grows or the demand for faster insights increases, additional nodes can be incorporated into the system seamlessly.

What sets MPP engines and databases apart from traditional databases is their architectural design. They use a shared...

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Authors (4)

BONNEFOY

BONNEFOY

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.

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Mehdi TAZI

Mehdi TAZI

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.

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Raphaël MANSUY

Raphaël MANSUY

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.

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CHAIZE

CHAIZE

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.

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