Data Warehousing & Business Intelligence Summit

AI Agents – a Pragmatic Approach

Conversational chatbots like ChatGPT were just the beginning. The real revolution lies in Autonomous AI Agents. This workshop by Thomas Gijsels bridges the gap between passive chat and active enterprise solutions. Designed for IT and Data professionals, this course covers the most recent developments including Multi-Agent systems, Agentic RAG, and MCP protocols. Learn to architect, secure, and deploy production-ready agents, to scale your impact and build the future of autonomous intelligence. During the workshop, you will build various AI Agents in a low-code tool. No development skills required.

Grounded AI in Data Warehousing

Hallucinations from AI can destroy trust in BI outputs. This hands-on technical session walks through building an LLM-powered analytics assistant that only answers from governed, verified data. With exercises that you will run from you own laptop.

Concept Modelling for Business Analysts

[Half day] This workshop by Alec Sharp introduces concept modelling from a non-technical perspective, provides tips and guidelines for the analyst, and explores entity-relationship modelling at conceptual and logical levels using techniques that maximise client engagement and understanding.

Data Governance Sprint

Struggling with data governance implementation or team alignment? This game-changing seminar introduces the Data Governance Sprint — an efficient, structured approach to kick-start and sustain your data governance initiatives with confidence!

Data Mesh Information Architecture: modeling data products and domains

This workshop addresses information architecture in decentralized data environments. It examines how domains document and share data, explores conceptual and logical modeling for clarity and interoperability, and provides practical exercises to design data products aligned with domain semantics.

AI Governance, Responsible AI and Data Governance: Connecting the Dots

Unlock the future of trustworthy AI. This seminar helps you connect AI Governance, Responsible AI, and Data Governance into one actionable framework. Learn how to mitigate risks, ensure compliance, and embed transparency, fairness, and accountability in AI initiatives. Packed with real-world examples and practical tools, this session is ideal for leaders who want to align innovation with ethics and create lasting business value.

Data Management Fundamentals

The DAMA DMBoK2 describes 11 disciplines of Data Management, with Data Governance being at the heart of all of these. The Certified Data Management Professional (CDMP) qualification provides a pathway for the introductory level (Associate) through higher levels of attainment. This course provides you with the knowledge, methods and techniques required to analyse, mature and implement information management solutions within your organisation. It gives a solid grounding in all the different disciplines of Data Management. Additionally, this course by Winfried Etzel prepares for the CDMP Data Management Fundamentals (DMF) examination.

Ontwerpen van een Nieuwe Data Architectuur

Organizations need data science, self-service BI, embedded BI, edge analytics, and customer-driven BI. For many, it is the key reason to develop a new, future-proof data architecture. This two-day seminar discusses how to design a modern data architecture. Guidelines, roadmaps, design criteria, tips, design rules, use cases, case studies, and practical examples are discussed extensively.

Agile Data Warehouse Design & Dimensional Modeling

A 3-day dimensional data modelling course presented internationally by leading data warehousing expert and author Lawrence Corr, covering the latest agile techniques for systematically gathering Business Intelligence (BI) requirements and designing effective DW/BI systems. Practical, hands-on workshop based on 7W, star schema and BEAM approach.

Business-oriented Data Modelling Masterclass

This highly participative data modelling workshop by Alec Sharp covers Entity-Relationship modelling from a non-technical perspective, provides tips and guidelines for the analyst, and explores contextual, conceptual, and detailed modelling techniques that maximize user involvement. It provides techniques for improving communication between data modelers and subject matter experts. Topics will be covered with a discussion of the issue, a review of guidelines and examples, a workshop exercise, and a group solution and debriefing.