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The Definitive Guide to Data Integration

The Definitive Guide to Data Integration

By : BONNEFOY, CHAIZE, Raphaël MANSUY, Mehdi TAZI
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The Definitive Guide to Data Integration

The Definitive Guide to Data Integration

By: BONNEFOY, CHAIZE, Raphaël MANSUY, Mehdi TAZI

Overview of this book

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.
Table of Contents (19 chapters)
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Data Integration Techniques

This chapter provides a thorough investigation into the vast landscape of strategies and methodologies used to consolidate disparate data sources into a unified, accessible format. The first part of this chapter introduces two prominent data integration models – point-to-point and middleware-based integration. Each model’s benefits, drawbacks, and use cases will be meticulously examined to offer you a nuanced understanding of their application in diverse contexts.

This chapter will then transition into a detailed exploration of various data integration architectures, namely batch, micro-batching, real-time, and incremental. Each architecture will be dissected to present you with their unique advantages, trade-offs, and potential applications, thereby providing a comprehensive view of their roles and performances in the data integration domain.

Then, this chapter will delve into commonly used data integration patterns, such as Extract...

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