[DSC DACH 25] Stefan Stricker-Agentic_BI.pptx

Most organizations are eager to unleash generative-AI and autonomous agents on their data, yet few stop to ask whether that data is consumable, trustworthy, and rich in business context. This session makes the case for treating “data as a product” as the missing link. We’ll explore how product thinking transforms scattered tables into well-governed, high-quality assets that AI agents can actually reason over. You’ll see concrete patterns for embedding metadata and semantics that give agents the context they need to surface insights, explain them, and even act on them. The payoff: faster time to insight, stronger data governance, and a leap in data literacy that lets non-experts ask natural-language questions and make confident, data-driven decisions.

1. Agentic BI: How Great Data Products Power AI Agents © TGW Logistics | 2025 1 Stefan Stricker TGW Logistics

2. OUR Roots In 1969 , Ludwig Szinicz and Heinz König established TGW Logistics in Wels, Austria, starting with a team of 10 employees. Recognized as pioneers and innovators, they have been at the forefront of developments in the roller conveyor industry. The Origins of It All Discover our DNA Powerful Intralogistics Technologies

3. Gründung von TGW Logistics Erstes Mustang Regalbediengerät Erster Schritt zur Software Strategiewechsel zu TGW Logistics als Systemintegrator Das Stingray Shuttle erobert den Markt KingDrive ®-Fördertechnik setzt auf getriebelose Motorrollen Mit FlashPick ® präsentiert TGW Logistics die innovative GTP-Lösung Die Robotiklösung Rovolution bietet vollautomatisches Kommissionieren, ist intelligent und selbstlernend Markteinführung der Taschensorterlösung OmniPick Der Digital Twin macht digitale Umgebungen sichtbar, nachvollziehbar und vorhersehbar Automatisierungslücken schließen || Digitalisierung Selbstoptimierende & selbstheilende Systeme 1969 1989 1994 2007 2011 2013 2016 2018 2019 2020 2025 2030 OUR Roots The Origins of It All

4. Lifetime Services One stop solution provider © TGW Logistics | 2025 4 Where we are now Integrated Logistics Solutions Logistics IT and Software Mechatronic Equipment

5. Example Company Brownfield omnichannel solution Enabled consolidation of two DCs Phase 2 will double the performance Phase1: 2,850 order lines/hr. 3 shuttles aisles | 44,100 storage locations Solution footprint: 50,000 sq. ft. Go-live July 2025 5 © TGW Logistics | 2025

6. The GAP Data swamp Not findable Hard to access Poor data quality Lack of organization Outdated data Inconsistent formats

7. Filling the gap Data Garden Easily accessible Well organized High quality Single source of truth Connected and shareable Rich metadata Modern and scalable systems Standardized formats Policies are in place

8. © TGW Logistics | 2025 8 DATA AS A PRODUCT DatA democratization

9. DatA Product User oriented Product Owner FAIR Findable Accessible Interoperable Resuable High quality and trust Lifecycle

10. Data Democratization Governance Data catalog Standardized data Data literacy Technological integration Drives innovation

11. Agentic BI 🔎 Autonomous Insights – Agents proactively surface trends , anomalies , and opportunities . 💬 Conversational Access – Natural language queries , context -aware answers . ⚡ Action-Driven – Moves beyond dashboards ; agents recommend or trigger actions . 🌍 Data Democratization – Empowers every business user with self-serve intelligence . From dashboards to decisions Agentic BI combines AI-powered agents with trusted data products to deliver insights and actions for everyone, not just analysts.

12. Why Data Products & Context Matter Data Products • Curated, reusable, trustworthy datasets. • Clear ownership, quality, and purpose. • Consistency across analytics, AI, and operations. Context for Agents • Agents need business meaning, not raw tables. • Metadata, lineage, and rules provide guardrails. • Context ensures relevance, explainability, and actionability. Semantic Layer (the translation engine) • Defines business terms (Revenue, Churn, Active User) in a common language. • Acts as the contract between data products and users/agents. • Powers self-service analytics by aligning data © TGW Logistics | 2025 12 The foundation for Agentic BI

13. Data Product Development Process © TGW Logistics | 2025 13 From Process to KPIs: A Universal Approach ⚙️ 🔀 📊 Define the Process Capture how the process works Align with objectives of process Process Data map Identify data sources , dependencies and transformations Document ownership and context Derive KPIs Translates activities into measurable indicators Document calculation logic

14. Data Product User Groups © TGW Logistics | 2025 14 Producer Consumer

15. Architecture © TGW Logistics | 2025 15

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20. THANK YOU © TGW Logistics | 2025 20