Our data observability platform
Kensu monitors the end-to-end quality of data usage in real-time so your team can easily prevent "datastrophes."
Understand your data usage
It is more important to understand what you do with your data than the data itself.
Analyse data quality and lineage through a single comprehensive view.
Get real-time insights about data usage across all your systems, projects and applications.
Monitor data flows instead of the ever-increasing number of repositories.
Share lineages, schemas and quality info with catalogs, glossaries and incident management systems.
At a glance, find the root causes of complex data issues to prevent any "datastrophes" from propagating.
Generate notifications about specific data events and their context.
Understand how data has been collected, copied and modified by any application.
Detection of AI-based anomalies
Detect anomalies based on historical data information.
Leverage lineage and historical data information to find the initial cause.
Make sure the quality of your data remains consistent at all times across your projects and applications.
Define your own rules and thresholds to anticipate data issues.
Set data quality objectives for your applications and projects.
Mitigate the impact of dependencies between teams.
Enable data quality monitoring within your application code.
We love your stack ...
... and we've got your back
Because security matters to us and to our clients, we are SOC 2 compliant.
We provide an on-premise solution for corporations with specific needs.
You can benefit from all our features with a highly secured cloud solution.
Discover our data observability method
The “Data Observability Driven Development” method is a paradigm shift that allows data teams and data usage to scale efficiently.
Data observability is done from within the applications instead of outside to enable your data projects with continuous validation, contextual observability, avoidance of work duplication, and iterative implementation.