Knowledge Cast by Enterprise Knowledge
Sep 25, 2026 · 17 min · 11 segments
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Malcolm Hawker, CDO of Profisee and panelist at this year's Semantic Layer Symposium, about semantic layer…
Malcolm HawkerGuest
Lulit TesfayeHost
And I want to go back to your talk about context, the context type that you mentioned.
You always ground your conversations and talk about business value, what problem are we solving, that mindset of becoming more outcome oriented, which is really what I appreciate is the focus of your book too, right? The Data Hero Playbook.
But to the contrary today, I think we're seeing a flash from the past where technology, especially in the data space, is consolidating.
Where are you seeing, to your point about semantic layer is here to stay, where are you seeing the semantic layer conversations losing the plot and becoming technology projects?
Even how we describe this thing, we're losing the plot when we go deep on jargon, when we split hairs around what does context mean? What does the semantic layer mean? Every time I post something on LinkedIn related to semantic layers or unstructured data, There is inevitably these rabbit holes that form within the LinkedIn threads that go into the abyss of how we think about context, how we think about semantic layers, how we approach library science, how we get into these back and forths about ontologies versus knowledge graphs.
So one of the bigger roadblocks is just simply falling into these semantic traps, these semantic rabbit holes that have nothing to do with solving business problems, that have nothing to do with enabling AI at scale.
The second one is something you already articulated, is we fail consistently to make a meaningful connection between the things that we know are important.
Like the capabilities that we know are important, writ large, knowledge management, data management, data governance, all of those critical capabilities.
We know that they're important, but then we fail to make a meaningful connection between those things and actual business outcomes.
That's an intangible that who doesn't want more insights? It's like, do you want some sprinkles on your banana split? Of course I want sprinkles.
We need to go beyond the kind of the pithy buzzwords and into things like cost of goods sold, lower cost of inventory.
How does knowledge management, data management, and the concept of context writ large, how does those things actually enable business outcomes? That's another way that we continue to shoot ourselves in the foot.
And I want to go back to your talk about context, the context type that you mentioned.
You always ground your conversations and talk about business value, what problem are we solving, that mindset of becoming more outcome oriented, which is really what I appreciate is the focus of your book too, right? The Data Hero Playbook.
But to the contrary today, I think we're seeing a flash from the past where technology, especially in the data space, is consolidating.
Where are you seeing, to your point about semantic layer is here to stay, where are you seeing the semantic layer conversations losing the plot and becoming technology projects?
Even how we describe this thing, we're losing the plot when we go deep on jargon, when we split hairs around what does context mean? What does the semantic layer mean? Every time I post something on LinkedIn related to semantic layers or unstructured data, There is inevitably these rabbit holes that form within the LinkedIn threads that go into the abyss of how we think about context, how we think about semantic layers, how we approach library science, how we get into these back and forths about ontologies versus knowledge graphs.
So one of the bigger roadblocks is just simply falling into these semantic traps, these semantic rabbit holes that have nothing to do with solving business problems, that have nothing to do with enabling AI at scale.
The second one is something you already articulated, is we fail consistently to make a meaningful connection between the things that we know are important.
Like the capabilities that we know are important, writ large, knowledge management, data management, data governance, all of those critical capabilities.
We know that they're important, but then we fail to make a meaningful connection between those things and actual business outcomes.
That's an intangible that who doesn't want more insights? It's like, do you want some sprinkles on your banana split? Of course I want sprinkles.
We need to go beyond the kind of the pithy buzzwords and into things like cost of goods sold, lower cost of inventory.
How does knowledge management, data management, and the concept of context writ large, how does those things actually enable business outcomes? That's another way that we continue to shoot ourselves in the foot.
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