Graphenus facilitates the implementation of discovery, observation and governance The data management system is based on the platform's own components as well as on external systems, enabling an integrated management of the data lifecycle throughout the organisation.
The platform supports metadata ingestion from over 50 data sources.
Possibility of incorporating new metadata sources through ad-hoc developments.
Push-based and pull-based mechanisms for dynamic incorporation of metadata.
Dynamic processing of metadata prior to ingestion (parameterisable & programmable)
End-to-end governance capability
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Definition of information domains, glossary of terms and dynamic tags for tagging data.
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Full traceability and historification of changes.
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User front-end and integration with other tools such as slack.
Proactive management: dynamic response to metadata changes
- API integration and metadata change event notification available.
- Integration of data governance in event-driven architectures.
- Impact analysis of changes in data.
Graphenus is based on a multi-tier architecture that integrates the best opensource tools at each level:
- Automatic metadata ingestion: the provisioning of metadata from different information sources and processing systems can be done either manually or automatically.
- By dynamically navigating through metadata it is possible to carry out Discovery activities in datasets, dashboards, artificial intelligence models and ETL processes.
- Graphenus integrates Datahub into the platform's security architecture.
- It is possible to define dictionaries of business terms in a hierarchical way, and associate them with the organisation's data governance organisational structure.
- Disruptive architecture: Datahub follows the push-based pattern, which facilitates continuous updating of metadata, making it easy to scale to any level.
