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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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Workflow Management, Monitoring, and Data Quality

In this chapter, we will delve into the crucial components of workflow management, event management, and data quality within the context of data integration. We will explore the fundamental concepts and significance of efficient workflow and event management in orchestrating data integration processes seamlessly. Key components such as workflow design, execution, scheduling, automation, error handling, and recovery will be discussed, along with best practices to ensure smooth and effective workflow management.

Event-driven architecture emerges as a powerful paradigm for event management, enabling real-time event processing, routing, monitoring, and alerting. We also explore the various monitoring techniques and tools that are essential for keeping a close eye on data integration workflows and ensuring their smooth functioning.

Data quality and data observability take center stage as vital factors for maintaining high-quality data...

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