What is Euno?
Euno provides active metadata management solutions aimed at improving the effectiveness of Business Intelligence (BI) and Artificial Intelligence (AI) initiatives. It works by connecting how data is modeled with how it is actually utilized within an organization. The platform offers an automated metadata catalog, which helps users understand analyst creations in BI tools, trace data lineage back to the source layer, and monitor field-level utilization. This facilitates the identification of key terms, resolution of conflicts, and removal of unused data models.
The tool assists in establishing and maintaining a governed source of truth by enabling the migration of key measures, originally created in BI tools like Tableau and Looker, into dbt (data build tool). It supports automated synchronization for direct querying by BI tools, ensuring consistency. Furthermore, Euno automates the certification of data products for both BI and AI applications based on customizable rules concerning dependencies on dbt models, governed metrics, and dataset compliance. This focus on governance helps ensure that AI agents and business analysts rely on trustworthy, up-to-date data through well-maintained semantic models and built-in automation.
Features
- Automated Metadata Catalog: Understand BI tool creations, lineage to the data layer, and field-level utilization.
- Governed Source of Truth: Establish and maintain a single source of truth by shifting measures into dbt and enabling automated sync.
- AI and BI Readiness Certification: Automatically certify data products based on custom rules (dependencies, metrics, compliance).
- Governance Programs: Includes Optimization (decluttering, cost-cutting), Certification (rule enforcement), and Metrics SOT (semantic model management).
- EQL Query Language: Query metadata for actionable insights (e.g., finding unused jobs, non-certified dashboards).
- Seamless Integration: Connects with modern data stacks like dbt, Looker, and Tableau.
Use Cases
- Improving data trustworthiness for BI and AI applications.
- Establishing a consistent source of truth across data and BI layers.
- Governing data models and ensuring compliance.
- Optimizing data environments by removing unused resources.
- Certifying dashboards and data products based on defined rules.
- Managing and scaling semantic models.
- Enabling analysts and engineers to sync dbt and BI tools effectively.
