Euno provides a centralized platform for data teams to visualize and manage data models across their stack, integrating with dbt to automate the synchronization of business logic from BI tools like Looker and Tableau. This approach addresses the challenge of maintaining consistent and governed data models in dynamic environments, enabling analysts to focus on business insights while ensuring reliable data governance.
Funding
$6.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Data teams struggle to maintain consistent and governed data models across their entire stack, especially when business logic is created in siloed BI tools. This leads to inconsistencies, conflicts, and duplicates, hindering self-service analytics and increasing the risk of unreliable insights. The challenge is to enable analysts to work independently while ensuring that their contributions are captured and integrated into a unified, governed data model.
Solution
Euno provides a centralized platform for data teams to visualize, manage, and build data models across their entire stack, automating the synchronization of business logic from BI tools like Looker and Tableau into dbt. The platform discovers business logic across the data environment, providing a unified logic catalog with end-to-end lineage and utilization metrics. It allows analysts to shift measures, dimensions, and custom tables from the BI layer to dbt, while automated guardrails detect duplicates, conflicts, and breaches of modeling principles. By enabling a reverse flow of business logic from BI tools to dbt, Euno empowers analysts to contribute to the data model evolution safely and efficiently, ensuring consistent data models at any scale.
Target Audience
Euno targets data teams, including data engineers, analytics engineers, and business analysts, who are looking to govern data models, enable self-service analytics, and maintain consistency across their data stack.
Features
- Automated business logic discovery across the data stack
- End-to-end lineage tracking and utilization metrics for data models
- Rapid promotion of measures, dimensions, and custom tables from BI tools to dbt
- Automated detection of duplicates, conflicts, and breaches of modeling principles
- Seamless integration with modern data stack components
- Unified logic catalog for exploring and managing data models
- Collaborative workflows for coordinating between analytics engineers and business analysts