Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
The Definitive Guide to Data Integration

You're reading from   The Definitive Guide to Data Integration Unlock the power of data integration to efficiently manage, transform, and analyze data

Arrow left icon
Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781837631919
Length 490 pages
Edition 1st Edition
Arrow right icon
Authors (4):
Arrow left icon
Raphaël MANSUY Raphaël MANSUY
Author Profile Icon Raphaël MANSUY
Raphaël MANSUY
Pierre-Yves BONNEFOY Pierre-Yves BONNEFOY
Author Profile Icon Pierre-Yves BONNEFOY
Pierre-Yves BONNEFOY
Emeric CHAIZE Emeric CHAIZE
Author Profile Icon Emeric CHAIZE
Emeric CHAIZE
Mehdi TAZI Mehdi TAZI
Author Profile Icon Mehdi TAZI
Mehdi TAZI
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Chapter 1: Introduction to Our Data Integration Journey 2. Chapter 2: Introducing Data Integration FREE CHAPTER 3. Chapter 3: Architecture and History of Data Integration 4. Chapter 4: Data Sources and Types 5. Chapter 5: Columnar Data Formats and Comparisons 6. Chapter 6: Data Storage Technologies and Architectures 7. Chapter 7: Data Ingestion and Storage Strategies 8. Chapter 8: Data Integration Techniques 9. Chapter 9: Data Transformation and Processing 10. Chapter 10: Transformation Patterns, Cleansing, and Normalization 11. Chapter 11: Data Exposition and APIs 12. Chapter 12: Data Preparation and Analysis 13. Chapter 13: Workflow Management, Monitoring, and Data Quality 14. Chapter 14: Lineage, Governance, and Compliance 15. Chapter 15: Various Architecture Use Cases 16. Chapter 16: Prospects and Challenges 17. Index 18. Other Books You May Enjoy

Understanding data quality and data observability

Data quality and data observability are two vital and interconnected facets of robust data management strategies. Ensuring data quality involves various techniques and methodologies to enhance the accuracy, consistency, completeness, and relevance of data. On the other hand, data observability involves providing visibility into the data pipeline, allowing organizations to trace data’s journey, detect anomalies, and ensure its reliability. Together, these elements help enterprises build a strong data foundation, leading to more reliable insights and informed decision-making.

Introduction to data quality and observability

Data quality and observability form the backbone of reliable and insightful data analytics. When we speak of data quality, we are referring to the degree of excellence exhibited in the data content using various dimensions, such as accuracy, consistency, completeness, and reliability. Data observability...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime