Organizations invest significant time and expertise building business glossaries, defining important concepts, and curating governance metadata in Collibra. This work creates valuable business context, but that context does not always flow easily into data architecture and data modeling processes.
Data architects and modelers may still need to manually interpret business terms, recreate definitions, identify potential entities and attributes, and establish relationships before a logical data model can begin to take shape.
In this on-demand webinar, Tim Rone demonstrates how ER/Studio’s AI Model Builder can use Collibra-curated metadata to accelerate logical data model creation. The session shows how trusted business knowledge can become entities, attributes, relationships, and other foundational modeling components in minutes.
Viewers will also learn how an AI-assisted workflow can reduce repetitive work while preserving the role of data architects and modelers in reviewing, refining, and validating the resulting design.
By connecting data governance metadata with logical data modeling, organizations can create a more consistent path from business meaning to technical design.
This on-demand webinar is designed for data architects, enterprise architects, data modelers, Collibra users, data governance leaders, metadata managers, database designers, data engineers, analytics leaders, and technical teams exploring practical applications of AI for data modeling and enterprise architecture.
Tim Rone
Lead Solutions Architect
Watch this recorded demonstration to learn how ER/Studio’s AI Model Builder can turn Collibra-curated metadata into logical data models and help teams connect governance knowledge with data architecture.
This webinar demonstrates how ER/Studio’s AI Model Builder can use business terms, definitions, and governance metadata curated in Collibra to generate foundational logical data model components.
Collibra metadata can provide trusted business terms, definitions, and governance context. ER/Studio’s AI Model Builder can use that information as a starting point for identifying logical entities, attributes, relationships, and model definitions.
No. AI-assisted model creation provides a starting point that data architects and modelers can review, refine, and validate. Human expertise remains important for confirming business meaning, model quality, relationships, and design decisions.
The webinar focuses on using curated metadata to generate foundational logical modeling components, including entities, attributes, relationships, and supporting definitions.
Connecting the two disciplines helps teams carry trusted business meaning into data design. This can reduce duplicated work, improve consistency, and support better collaboration between governance professionals and data architects.
The session is relevant to data architects, modelers, Collibra users, governance leaders, metadata professionals, enterprise architects, and teams exploring AI-assisted data architecture workflows.
Explore ER/Studio resources or contact the ER/Studio team to discuss your data modeling, metadata management, governance, and architecture requirements.
Connect with our team to explore how ER/Studio can help your organization turn trusted metadata into actionable data models and strengthen alignment between governance and architecture.
