Data Observability: Ensuring Trust in Data Pipelines

Abstract

Data observability is the key process you need to implement to guarantee the consistency of the data pipeline in terms of credibility. The features of data quality, data freshness, lineage, and schema changes checked in real-time help prevent problems before they accumulate, and impact the data pipeline. As the field of data observability is still in its infancy, this paper aims at identifying which components it could be composed of, what tools it could ideally comprise, and what value it can bring to businesses, with an accentuation of recommendations for its implementation in contemporary data workloads.

Keywords: Data visibility, data accuracy, datasets delivery, constant monitoring, data origin, schema evolution, outliers, decision making process, risks management, work productivity