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The Definitive Guide to Data Integration
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The Definitive Guide to Data Integration
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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)
Preface
Chapter 1: Introduction to Our Data Integration Journey
Chapter 2: Introducing Data Integration
Chapter 3: Architecture and History of Data Integration
Chapter 4: Data Sources and Types
Chapter 5: Columnar Data Formats and Comparisons
Chapter 6: Data Storage Technologies and Architectures
Chapter 7: Data Ingestion and Storage Strategies
Chapter 8: Data Integration Techniques
Chapter 9: Data Transformation and Processing
Chapter 10: Transformation Patterns, Cleansing, and Normalization
Chapter 11: Data Exposition and APIs
Chapter 12: Data Preparation and Analysis
Chapter 13: Workflow Management, Monitoring, and Data Quality
Chapter 14: Lineage, Governance, and Compliance
Chapter 15: Various Architecture Use Cases
Chapter 16: Prospects and Challenges
Index
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