When
Tuesday, 23 June 2026 to Thursday, 25 June 2026
Where
MOC Munich
What to expect
- Over 130 expert sessions and keynotes on Data & AI
- Personalized strategy consulting for your data architecture at the Woodmark booth
- Talk on building a sports data platform using the example of Woodmark and FC Augsburg
- Interactive deep dives and hands-on workshops for all experience levels
- Top-tier networking with the leading analytics community
Who is TDWI for?
- Data & IT Professionals:
Architects, engineers, analysts, and data scientists. - Strategic Decision-Makers:
CDOs, project managers, and heads of BI & analytics centers. - Industry Pioneers:
Companies putting cloud migration, governance, or GenAI into practice. - Knowledge Seekers:
Beginners to experts looking for vendor-independent expertise.
Agenda
TDWI Munich | ProgramWhy it’s worth attending
TDWI Munich 2026 is the key platform to take your data strategy to the next level. Take the opportunity to translate valuable insights from the sessions directly into concrete solutions: get inspired by the latest trends and visit us afterwards at our booth to discuss your individual roadmaps for analytics, cloud, and AI with our experts. We look forward to actively shaping your company’s digital transformation together with you.
👉 Secure your appointment now for a personal expert consultation at TDWI Munich 2026.
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Speakers
Tom Wysotzki
Head of Data / FC Augsburg 1907 GmbH & Co. KGaA
Tom Wysotzki leads the Data & Analytics team at FC Augsburg and is responsible for the strategic and operational development of the club’s entire data infrastructure. His team builds cloud-based data pipelines on AWS as well as analytical applications that provide the coaching staff, scouting, and management with decision-relevant insights—from match analysis and scouting evaluations to business analytics.
Ece Kilkeser
Senior BI Engineer / AutoScout24
An overview of AutoScout24’s migration from MicroStrategy to Amazon QuickSight, highlighting key challenges encountered during the transition and the improvements achieved post-migration, including enhanced data governance, stronger data quality enforcement, and the enablement of AI-driven insights.