Hi Joe. I equate the semantic model to the combination for the LDM and PDM content. I know that in BI reporting tools such as OBI, Power BI and many others the term semantic model comes up as well. As an example a star schema LDM and PDM metadata content can be imported into or integrated between a data modeling tool and the reporting tool to reduce time spent re-developing all the attribute names, relationships, etc. Would love to talk more on this!
Love this framing, Joe. Semantics really is the connective tissue between human intent and machine execution. The controlled vocabulary <=> thesaurus distinction (and the “client vs customer” example) matches what we see derailing projects and LLM prompts alike. Biggest wins come from making metrics/dimensions first‑class with clear metadata and lineage. Curious how you draw the line between BI “semantic models” and broader enterprise semantics. Looking forward to the taxonomy section.
Anecdotally, vocabulary semantics is a recurring bottleneck in large enterprises regardless if driven by a transformation initiative or not.
That’s because without a common language between people across disciplines, very tine-consuming and/or nearly impossible to communicate, collaboratively iterate solutions, triage issues, etc.
This is one reason of many why having updated, multidisciplinary context is foundational for short and long term continuity.
Hi Joe. I equate the semantic model to the combination for the LDM and PDM content. I know that in BI reporting tools such as OBI, Power BI and many others the term semantic model comes up as well. As an example a star schema LDM and PDM metadata content can be imported into or integrated between a data modeling tool and the reporting tool to reduce time spent re-developing all the attribute names, relationships, etc. Would love to talk more on this!
Thank you, super helpful to me, as a Marketer! 🫶
Love this framing, Joe. Semantics really is the connective tissue between human intent and machine execution. The controlled vocabulary <=> thesaurus distinction (and the “client vs customer” example) matches what we see derailing projects and LLM prompts alike. Biggest wins come from making metrics/dimensions first‑class with clear metadata and lineage. Curious how you draw the line between BI “semantic models” and broader enterprise semantics. Looking forward to the taxonomy section.
Anecdotally, vocabulary semantics is a recurring bottleneck in large enterprises regardless if driven by a transformation initiative or not.
That’s because without a common language between people across disciplines, very tine-consuming and/or nearly impossible to communicate, collaboratively iterate solutions, triage issues, etc.
This is one reason of many why having updated, multidisciplinary context is foundational for short and long term continuity.