Stop Waiting for Data to Break Things
Poor data quality costs time, trust, and money. Most tools try to fix things after the damage is done. Conduktor Trust enforces data quality where streaming starts—before it enters your pipelines—so issues are detected early and are stopped in their tracks.
Without Trust in Your Data
Data teams discover quality issues days later.
Developers carry the burden of governance.
AI models train and make predictions on broken data.
Analytics and other systems run on polluted streams.
With Conduktor Trust
Quality can be enforced before the data flows.
Visibility is centralized across teams.
AI training and inference are protected from bad data.
Müheloser Kafka-Selbstservice in 4 Schritten
Entwicklerautonomie aktivieren
Skalieren Sie selbstbewusst
Sicherheit und Governance durchsetzen
Datenmanagement in großem Maßstab
01
Define Rules
02
Apply Policies
03
Trigger actions
04
Gain insight
rules
How the data
is validated
Policies
Where the rule(s)
are applied
actions
What happens if the rule(s)
are violated
insight
Determine the frequency
of violations
What Makes Trust Different?
Most observability
tools sit downstream.
We don’t.
Producer-led enforcement
(Data Contracts)
Reactive Approach
(Monte Carlo)
Conduktor Trust
Works natively on streaming data
Proactively enforces data quality
Supports schema-less topics
Centralized policy control + local enforcement
limited
