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The Definitive Guide to Data Integration

You're reading from  The Definitive Guide to Data Integration

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781837631919
Pages 490 pages
Edition 1st Edition
Languages
Authors (4):
Pierre-Yves BONNEFOY Pierre-Yves BONNEFOY
Profile icon Pierre-Yves BONNEFOY
Emeric CHAIZE Emeric CHAIZE
Profile icon Emeric CHAIZE
Raphaël MANSUY Raphaël MANSUY
Profile icon Raphaël MANSUY
Mehdi TAZI Mehdi TAZI
Profile icon Mehdi TAZI
View More author details

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 Other Books You May Enjoy

Summary

In this chapter, we explored the critical components and best practices for data preparation and analysis. Starting with an examination of the importance and components of data preparation, we delved into the factors influencing when and where to perform data preparation, highlighting the need for considering data quality, scalability, storage, governance, and accessibility.

The chapter then transitioned into the strategy and choice of transformations. A detailed discussion was conducted on how to develop a data transformation strategy, the considerations for selecting appropriate data transformations, and the implementation and optimization of these transformations. The main emphasis was on understanding data requirements, assessing data quality and performance, and aligning the strategy with analytics and reporting goals.

In the final section, we dealt with the key concepts for reporting and self-analysis, where we discussed how to design effective reports, ensure data...

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