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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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Various Architecture Use Cases

In this book, we have journeyed through the intricacies of data integration, and this chapter is the culmination of all the knowledge amassed. Here, we dive into the practical application of the principles and techniques discussed throughout the preceding chapters.

This chapter explores various data integration architectures for real-time, cloud, geospatial, and IoT analysis. Each use case presents the unique requirements and challenges stemming from diverse data sources and business needs based on our own experience. Proper tools, techniques, and architectural patterns empower effective integration, but factors such as scalability, heterogeneity, spatial relationships, and security must be addressed. By choosing optimal architectures tailored to specific integration needs, organizations can harness data-driven insights across pivotal domains. Looking ahead, emerging trends, such as machine learning and new technologies, will shape the data integration...

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