Discover an approach to better monitoring of data systems with the book Fundamentals of Data Observability, which can help you better understand how to monitor and manage data quality within an organization.

Data are today a crucial part of how many companies operate, but without properly configured observability, managing them can be challenging. This book guides you through the fundamentals of data observability - a concept focused on monitoring, analyzing, and improving data pipelines, detecting issues early, and supporting the reliability of data systems. You will learn how to identify potential problems in data and how to address them before they affect downstream analyses.

Fundamentals of Data Observability offers a clear guide intended for data engineers, analysts, and leaders who want to get acquainted with the topic of managing and observing data flows. The book covers basic principles, common practices, and tools that can help you better understand how to keep data processes under control and increase the trustworthiness of data for decision-making.

Why buy this book?

• You can improve monitoring and data system quality, which can support more informed decision-making
• You will gain a clearer understanding of data observability - an important area of modern data architecture
• It will help you better understand the risks of data errors that can lead to incomplete or inaccurate analyses
• You will learn about tools and methods for data management that can be considered and adapted to your specific environment
• The book can be useful for both novice and experienced readers in the field of data and IT (depending on their prior knowledge)

Main product features

• Covers foundational and advanced concepts of data observability
• Offers recommendations for implementing and managing data monitoring approaches
• Provides an overview of selected tools and technologies used in the data field
• Intended for IT professionals, data engineers, analysts, and managers
• Focuses on improving the quality and reliability of data pipelines within organizations