Build the Information Foundation for AI
AI initiatives often expose weaknesses that may have existed in enterprise data environments for years: unknown ownership, conflicting definitions, poor quality, missing lineage and duplicate entities. Datacogence helps organisations establish the information architecture required for trusted AI.
Core capabilities
Six capabilities. One information foundation.
Implemented as an integrated layer rather than six disconnected tools with six disconnected owners.
Data Catalogue
Discover what data exists, where it resides, what it means and who owns it.
02Data Lineage
Trace data from source through transformation to consumption so teams can understand dependencies and impact.
03Business Glossary
Create a common language across business and technology by defining critical business terms, metrics and concepts.
04Data Quality
Define, measure and improve critical data quality dimensions across the information lifecycle.
05Master Data Management
Establish trusted representations of critical business entities and reduce duplication and inconsistency.
06Organisational Metamodel
Model the relationships between organisational structures, functions, roles, processes, systems, data and accountability.
Philosophy
Governance that enables AI.
Governance should enable AI, not become another layer of bureaucracy around it.
Make it visible enough to be trusted.
Our objective is to make ownership, meaning, quality and accountability visible enough that teams can use data with confidence.
Next step
Assess your data governance foundation
Understand the governance gaps that may limit AI adoption and define a practical path to trusted data.