Organizations are collecting more data than ever, but data volume alone does not create trust. Inconsistent definitions, disconnected systems, unclear ownership, and limited business context still make it difficult for teams to use data confidently.
As AI becomes more embedded in analytics and decision-making, the need for trusted data becomes even more important. When teams do not agree on what data means, they cannot confidently stand behind the insights, reports, models, or AI outputs it produces.
A data product approach helps bridge the gap between raw data and business value by creating trusted, reusable, governed assets designed for consumption across the enterprise. But successful data products depend on a strong foundation of data modeling, business glossary management, metadata governance, ownership, stewardship, and collaboration.
In this recorded session, Angela Eberle shows how ER/Studio Enterprise Edition, Team Server Core, and governance integrations with Microsoft Purview and Collibra work together to help organizations create a shared language for data, connect business context to technical assets, and improve confidence in analytics, reporting, and AI initiatives.
This on-demand webinar is designed for data architects, data modelers, data governance leaders, data engineers, analytics leaders, database designers, business data owners, and AI stakeholders who want to improve trust, consistency, and usability across enterprise data assets.
Angela Eberle
ER/Studio Product Expert
Watch this recorded session to learn how ER/Studio can help your team build trusted data products that improve governance, strengthen collaboration, and increase confidence in analytics, reporting, and AI outcomes.
This webinar explains how organizations can build trusted data products by connecting data modeling, business glossary management, metadata governance, ownership, and collaboration. It shows how ER/Studio helps create a trusted foundation for analytics, reporting, and AI initiatives.
Trusted data products are reusable, governed data assets that include clear definitions, ownership, metadata, and business context. They help teams use data more confidently across reporting, analytics, decision-making, and AI workflows.
ER/Studio supports data product delivery by helping teams model data assets, manage business definitions, connect metadata, improve collaboration, and align business and technical stakeholders around a shared understanding of data.
ER/Studio helps data teams improve governance by supporting business glossary management, metadata visibility, ownership, stewardship, and integrations with governance platforms such as Microsoft Purview and Collibra.
AI outcomes depend on the quality, consistency, and meaning of the data behind them. Trusted data products help teams improve transparency, define ownership, and establish shared definitions so AI initiatives are built on better-governed data.
This session is valuable for data architects, data modelers, data governance professionals, analytics leaders, data engineers, business data owners, and teams preparing data foundations for AI and advanced analytics.
Connect with our team to learn how ER/Studio can help support data modeling, data governance, collaboration, metadata management, and trusted data product initiatives.
