Semantic Layer by Design: An Immersive One-Day Training
An exclusive training opportunity to accelerate the design and implementation of a semantic layer within your organization.
On Day 1 of the Semantic Layer Symposium 2026, join EK’s expert instructors for a hands-on, end-to-end enterprise semantic layer design training — delivering the most interactive and practitioner-focused experience in the field.
Over the course of the day, EK’s semantic solution experts will take you through each step of a successful semantic layer program. The training will detail the semantic layer framework and its components, specifically delving into ontologies, taxonomies, and knowledge graphs, as well as their pivotal roles in unlocking advanced semantics to bridge knowledge, content, data, and AI.
Grounded in EK’s Semantic Layer Framework
The same methodology being published in Bridging Knowledge, Data, and AI (Tesfaye, Hilger & Wahl) — refined through real-world implementations at the world’s most knowledge-intensive organizations, and now available as a full-day simulation experience.
Through hands-on exercises, attendees will learn foundational and advanced concepts in ontology design and knowledge graph integration, along with practical applications to improve data interoperability and enhance enterprise systems such as advanced search, content personalization, and AI-driven applications like chatbots, recommendation engines, and AI agents. The training will examine the practical implementation of semantic technologies, using real-world case studies and leading software products to illustrate how a semantic layer can be leveraged for data transformation and integration.
What You Will Learn
Semantic layer fundamentals & AI-readiness
Understanding taxonomies, ontologies, and LPG and RDF-based models, and how to design them for AI-ready content and downstream LLM integration.
Building & implementing knowledge graphs
Hands-on exercises to model, integrate, and query semantic data using the core Semantic Web standards: RDF, OWL, SKOS, SPARQL, and SHACL validation.
AI & machine learning integration
Leveraging semantic inference, auto-tagging, and graph machine learning techniques, with an eye toward agentic AI integration.
Use cases & business applications
Exploring real-world implementations across industries, from AI agent enablement and context engineering to 360-degree data and asset views.
Training Overview
Part 1
Semantic Layer Fundamentals
Foundational learning — guided instruction and discussion.
Understand the components of the semantic layer and how they solve for enterprise use cases.
Introduce the Semantic Layer Maturity Model and AI-Readiness Benchmark and understand how organizations can evolve their semantic layer capabilities over time.
Explore success stories across industries and learn how to scope and vision semantic layer products — including AI agent enablement and context graph applications.
Explore various types of semantic models (e.g., taxonomies, ontologies, graph schemas) and their key characteristics.
Understand the Semantic Web Standards frameworks and their applications.
Experience AI-assisted semantic design techniques, including LLM-generated model generation.
Examine common architectures, approaches for implementation, context engineering patterns, and AI & machine learning integration.
Understand typical program models and identify skillsets required to effectively engage with the organization at scale.
Part 2
Building a Semantic Layer
Hands-on simulation — collaborative breakouts, real-world design exercises, and peer learning.
Develop a holistic semantic product vision that bridges business needs with technical approaches.
Apply practical design approaches for user experiences and semantic models.
Incorporate AI-assisted design techniques.
Develop an implementable model and solutions architecture for the prioritized use case and build an actionable implementation plan for scale.
Address knowledge asset AI-readiness and agentic semantic data management.
Reflect on lessons learned and how these apply to your organization, walking away with actionable frameworks, reusable templates, and a peer network to support your organization’s semantic layer journey.
Business Outcomes
Build an AI-ready knowledge & data foundation
Organizations that invest in semantic layers today are the ones whose AI initiatives actually deliver tomorrow. Learn to design scalable, adaptive semantic architectures built for LLM integration, agentic AI pipelines, and evolving business needs — serving as the connective tissue between your knowledge, content, data, and AI systems.
Make better decisions, faster
You can’t act on data you don’t trust. Semantic structure is the path to more reliable data for your organization. Learn how to design and interpret knowledge structures that surface the right information, in the right context, at the right time — enabling smarter business intelligence and more trustworthy AI outputs.
Drive operational efficiency & quantifiable ROI
A semantic layer can cut the time employees spend searching, consolidate redundant software licenses, and eliminate duplicate research and data purchases. Learn how your organization can achieve this through hands-on ontology design and knowledge graph implementation.
Who Should Attend
Organizational leaders
CDOs, CDAIOs, and business executives looking to enhance critical insights through semantics and data standards.
Data modelers, scientists & engineers
Data modelers, scientists, and engineers involved in AI, machine learning, and data modeling initiatives.
Knowledge & data managers
Professionals seeking to understand how ontologies and knowledge graphs drive measurable business value.
IT professionals
IT professionals interested in implementing and managing semantic technologies at scale.