Table of Contents
Preface
Part 1: Introduction to Data Observability
1
Fundamentals of Data Quality Monitoring
Learning about the maturity path of data in companies
Identifying information bias in data
Data producers
Data consumers
The relationship between producers and consumers
Asymmetric information among stakeholders
Exploring the seven dimensions of data quality
Accuracy
Completeness
Consistency
Conformity
Integrity
Timeliness
Uniqueness
Consequences of data quality issues
Turning data quality into SLAs
An agreement as a starting point
The incumbent responsibilities of producers
Considerations for SLOs and SLAs
Indicators of data quality
Data source metadata
Schema
Lineage
Application
Statistics and KPIs
Examples of SLAs, SLOs, and SLIs ...
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