Your data investment, returned.

The data observability platform that gives your time back to you.

Konstellation Data Dashboard

Overwhelmed? We Get It.

Every day, data engineers and teams drown in a sea of issues, struggling to separate signal from noise. Instead of innovating, they're firefighting.

What is Konstellation

Konstellation detects, diagnoses, and prioritizes data issues automatically, easing the burden on data teams.

Out-of-the-box data quality, anomaly & incident detection, and timely alerting

Get standardized quality metrics for your data, out-of-the-box. Quickly understand how your data is changing, from row counts to nulls.

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Anomaly and Incident Detection

Let AI work for you. Konstellation's AI / ML capabilities detect anomalies in your data and clusters them into incidents based on root-cause analysis.

Zero Alert Fatigue

Fix What Matters. Konstellation understands each incident's real impact on your business so you get notified whenever it's worthy of your attention.

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Understand your data quality progress

Stay informed of your team's progress. Konstellation's customizable dashboards bring data health KPIs to you.

Deliver High-Quality Data at Scale

Fully Automated

Fully Automated

Our plug-and-play platform detects data issues and identifies root causes promptly.

ML-Driven Prioritization

ML-Driven Prioritization

The machine learning-based Criticality Score prioritizes incidents for you, based on business impact.

Extreme Efficiency

Extreme Efficiency

Rapidly increase efficiency in data operations and management across your team.

Stop Firefighting, Start Innovating.

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Learn More About Data Observability

Discover our resources to learn more!

Blog

Exploring Data Mesh - Benefits, Challenges, and Observability

Explore the benefits and challenges of adopting a data mesh architecture and its impact on your data strategy.

Webinar

Webinar #1: What is data observability?

ecording of Konstellation's webinar from May 2024. Konstellation is a data observability platform that solves data quality and reliability issues through ML-driven anomaly detection and incident prioritization.

Case Study

Transforming Data Quality for a Leading Streaming Platform

A major media and entertainment industry player, this customer had an ever-expanding user base and a growing data ecosystem.

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