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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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History of data integration

The biography of data integration is long, but we want to focus on a few key events to explain both current and future advancements in data integration, starting with mainframes up to the modern data stack.

Early data processing and mainframes

Before open source data platform software emerged, mainframes were the foundation for data processing in big organizations. These powerful computers managed huge amounts of data and completed complex calculations quickly. IBM’s System/360, introduced in 1964, was among the first influential mainframe computers and laid the groundwork for many business computing systems.

Mainframe technologies, such as COBOL and IMS, provided early solutions for data storage, management, and processing. Despite their high costs and proprietary nature, mainframes were widely adopted by organizations due to their reliability, security, and performance.

Expert advice

Mainframes are still used today by some large organizations...

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