Michael Liedl

(he/him)

Michael Liedl

Consultant

Business Analyst & Project Engineer

ABOUT THE SPEAKER

Michael Liedl is a Business Analyst, Software Project Engineer and Consultant with experience spanning technical support, requirements analysis, project management and customer-facing consultancy. He describes himself as an analytical thinker able to understand both business and technical sides of a problem, with a strong focus on identifying underlying requirements and delivering practical solutions. Michael has held long-term roles with Next Retail Ltd, American Express UK and Italy, and Alfabyte Srl, where he worked across technical support, business requirements analysis, project delivery and consultancy. His background combines technical understanding, communication skills and delivery experience, with a particular emphasis on solving complex IT challenges while maintaining quality and attention to detail.

Sessions

Oskar Holm

Michael Liedl

AI-Ready Data Pipelines: A Hands-On Introduction to dbt

AI is only as useful as the data it can trust. OVERVIEW As organisations move towards agents, automation and AI-assisted decision-making, the quality of the underlying data pipeline becomes critical. Businesses need data workflows that are clear, reliable, testable, documented and easy to maintain. Without that foundation, AI systems can become difficult to trust, difficult to scale and difficult to explain. This hands-on workshop introduces dbt, one of the tools changing how modern data teams build and manage data transformation. Participants will be guided through the basics of a modern data workflow, from setup through to a simple data-driven outcome. Along the way, the session will explore how data can be cleaned, transformed, tested and documented, and why lineage and maintainability are becoming increasingly important in AI-ready organisations. The workshop is designed to be beginner-friendly, with enough depth for more advanced questions on the day. WHAT PARTIPANTS WILL EXPLORE How modern data pipelines work Why dbt is becoming an important tool for data teams How data can be collected, cleaned, transformed and used to support decisions How testing, documentation and lineage help make data more trustworthy Why code-based, maintainable data workflows matter in the age of AI What skills and tools are useful for people looking to move further into data analysis or data engineering WHO IS IT FOR This workshop is for anyone curious about how modern data workflows are built. It will be especially useful for students and early-career learners interested in data, AI or analytics, founders and business leaders who want to understand what sits behind reliable AI systems, analysts, engineers or technical professionals who are curious about dbt, and anyone trying to understand what “AI-ready data” really means in practice. EXPERIENCE LEVEL This is a beginner-friendly workshop with room for more advanced questions. You do not need to be a data engineer to attend. Some familiarity with Python, SQL or Jupyter Notebooks will be helpful, but the session is designed to support a range of ability levels. PRACTICAL DETAILS Attendees should bring a laptop. Participants will receive a short setup guide in advance, including the tools and materials needed for the session. The teaching materials are designed so attendees can continue learning afterwards, with a study roadmap and links to further resources.

Oskar Holm

Michael Liedl

AI-Ready Data Pipelines: A Hands-On Introduction to dbt

AI is only as useful as the data it can trust. OVERVIEW As organisations move towards agents, automation and AI-assisted decision-making, the quality of the underlying data pipeline becomes critical. Businesses need data workflows that are clear, reliable, testable, documented and easy to maintain. Without that foundation, AI systems can become difficult to trust, difficult to scale and difficult to explain. This hands-on workshop introduces dbt, one of the tools changing how modern data teams build and manage data transformation. Participants will be guided through the basics of a modern data workflow, from setup through to a simple data-driven outcome. Along the way, the session will explore how data can be cleaned, transformed, tested and documented, and why lineage and maintainability are becoming increasingly important in AI-ready organisations. The workshop is designed to be beginner-friendly, with enough depth for more advanced questions on the day. WHAT PARTIPANTS WILL EXPLORE How modern data pipelines work Why dbt is becoming an important tool for data teams How data can be collected, cleaned, transformed and used to support decisions How testing, documentation and lineage help make data more trustworthy Why code-based, maintainable data workflows matter in the age of AI What skills and tools are useful for people looking to move further into data analysis or data engineering WHO IS IT FOR This workshop is for anyone curious about how modern data workflows are built. It will be especially useful for students and early-career learners interested in data, AI or analytics, founders and business leaders who want to understand what sits behind reliable AI systems, analysts, engineers or technical professionals who are curious about dbt, and anyone trying to understand what “AI-ready data” really means in practice. EXPERIENCE LEVEL This is a beginner-friendly workshop with room for more advanced questions. You do not need to be a data engineer to attend. Some familiarity with Python, SQL or Jupyter Notebooks will be helpful, but the session is designed to support a range of ability levels. PRACTICAL DETAILS Attendees should bring a laptop. Participants will receive a short setup guide in advance, including the tools and materials needed for the session. The teaching materials are designed so attendees can continue learning afterwards, with a study roadmap and links to further resources.