Summary
This white paper outlines a modern approach to achieving complete data observability without incurring excessive costs. It begins by explaining the necessity of data observability in organizations that manage vast amounts of data across various technologies. The document details how traditional quality controls are overwhelmed by the scale and speed of data movement, necessitating a new approach. It defines data observability as the ability to monitor data attributes such as size, freshness, uniqueness, correctness, completeness, and accuracy. The paper contrasts legacy and traditional methods with Actian's modern approach, which utilizes a decoupled data quality engine for continuous monitoring. This method allows for comprehensive observability across structured and semi-structured data sources, reducing costs and simplifying implementation. Additionally, the paper emphasizes the importance of data lineage in tracking data movement and quality across sources, ensuring that organizations can maintain high standards of data governance and compliance. Overall, it presents a framework for organizations to enhance their data management capabilities.
