What is Data Observability for Data Lakes?

In today's data-driven world, organizations are increasingly relying on data lakes to store large volumes of data from various sources. However, ensuring the quality and reliability of this data can be a major challenge. This is where data observability comes in – a tool that enables comprehensive monitoring, management, and analysis of data within a data lake environment.

Data observability involves collecting and centralizing telemetry data, such as logs, metrics, traces, and security events, from various sources to ensure data accuracy, reliability, and performance across the entire data ecosystem. By implementing data observability, organizations can proactively detect issues, optimize data workflows, and maintain high data quality within their data lakes.

Data observability is essential for data lakes because it provides a 360-degree view of an organization's data, allowing IT professionals to monitor system performance in real-time, standardize data, speed up performance issues, mitigate reliability issues, improve analytics, manage capacities, and increase efficiency and productivity.

Source: https://dev.to/first_eigen/what-is-data-observability-for-data-lakes-2k22