Kibana for Data Quality

Kibana is a monitoring tool primarily used for analyzing and visualizing logs and metrics. It is an integral part of the Elastic Stack (formerly ELK Stack), alongside Elasticsearch and Logstash. Kibana allows users to create charts, interactive dashboards, and reports based on data indexed in Elasticsearch, providing a powerful interface for exploring and analyzing logs in real-time.

While Kibana is effective for log management, using it for data quality monitoring comes with several limitations:

• Limited variety of visualizations: Kibana offers a restricted set of charts. For more customizable and insightful dashboards, third-party tools may be required.
• Lack of data preprocessing: Kibana does not support data manipulation or advanced aggregations without relying on external transformations.
• Steep learning curve: Users need to learn Vega and Kibana Query Language (KQL), and the lack of SQL support can be a barrier for beginners.

For more efficient data quality monitoring, alternatives like Elementary, which automatically visualizes dbt tests, or Sifflet, with its ready-to-use dashboards, may be more suitable. For customized tracking, a BI dashboard can also be a viable option.

Theodo’s point of view

A few years ago, we used Kibana for data quality monitoring. While it was effective for simple metrics, it proved too limited for more complex needs. We therefore recommend Kibana only for application log analysis and visualization.