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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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Understanding the strategic motives for data exposure

Exposing data from analytics platforms has become an integral part of modern data-driven operations. This process allows raw data from diverse sources, including databases, logs, IoT devices, and third-party APIs, to be accessed and analyzed centrally. As a result, it helps facilitate well-informed strategic decisions and propels business growth.

Data exposure between profiles

Within an analytics platform, the seamless and efficient exchange of data between various user profiles – such as data scientists, data analysts, and other stakeholders – is of paramount importance. These diverse roles, each with their unique requirements and perspectives, constitute the collective intelligence of an organization’s data operations.

Data scientists, for instance, often require raw, unfiltered data to build predictive models and explore intricate patterns and relationships within the data. On the other hand, data...

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