🧐What is Data observability: Basic Principles
Data observability is a new level in the modern data processing stack, providing data teams with transparency and quality. The goal of data observability is to reduce the chance of errors in business decisions due to incorrect information in the data.
Observability is ensured by the following principles:
Freshness indicates how fresh data structures are.
Distribution tells you if the data falls within the expected range.
Volume involves understanding the completeness of data structures and the state of data sources.
The schema allows you to understand who and when makes changes to data structures.
Lineage maps upstream data sources to downstream data sinks, helping you determine where errors or failures occurred.
More about data observability in the source: https://habr.com/ru/companies/otus/articles/559320/