As always, there will be plenty of time for networking, discussions, and snacks & drinks courtesy of our host.
📍 Event Details
📅 Date: Thursday, August 20th, 2026
📍 Venue: Giesinger Bräu Werk2
📫 Address: Detmoldstraße 40, 80935 München
🎤 Scaling Data, Enabling Agents: Finanz Informatik's Data Lakehouse Journey by Jannis Eickenroth & Christian Bandowski
Finanz Informatik is evolving its Data Analytics Platform into the central data foundation for Germany’s Sparkassen-Finanzgruppe. What started with a small group of early adopters is rapidly growing into a modern data lakehouse platform designed to serve hundreds of institutions under strict regulatory, security, and governance requirements. In this session, we share lessons learned from building a scalable lakehouse based on open standards, leveraging technologies such as Apache Iceberg, Starburst Enterprise Platform, and Lakekeeper. We discuss approaches for multi-tenancy, governed data access, and centralized governance in a highly regulated environment. As the platform expands, the next step is already taking shape: enabling users to interact with enterprise data through natural language instead of specialized technical skills. We will discuss why trusted data, governance, metadata, and open architectures are the key prerequisites for Agentic AI and how the existing lakehouse foundation is being extended towards conversational analytics and intelligent, data-aware agents. Attendees will gain practical insights into large-scale lakehouse architecture, governance at scale, and the journey from enterprise data platforms to Agentic AI.
About the speakers:
Christian Bandowski is a Team Lead and Big Data Architect at SVA, focusing on modern Data Lakehouse architectures and platform engineering. He supports organizations in building scalable data platforms across cloud, on-premises, and hybrid environments, helping them establish the foundations for data-driven and AI-powered solutions. With a background in software development and architecture, he applies software engineering best practices to data platforms, governance, and data engineering challenges. He is also actively involved in evaluating new technologies and establishing strategic partnerships in the Data Lakehouse ecosystem. His work focuses on delivering robust and governed platforms that can scale across teams, use cases, and business domains.
Jannis is Head of Analytics and Customer Engagement at Finanz Informatik, the central IT service provider of the Savings Banks Finance Group. He is responsible for the strategic use of data across the entire value chain – from data platforms and advanced analytics to AI-driven customer engagement. His goal is not just to make data available, but to turn it into tangible business value through integrated engagement management, data-driven decision-making, and a strong platform and architecture strategy. Previously, he led the Data Platform department and served as a project manager for the introduction of modern software technologies at Finanz Informatik. His technical background spans both mainframe and Java development. Jannis stands for pragmatic innovation, strategic thinking, and collaborative delivery
🎤 When architecture becomes executable: why modern data platforms need an Architecture Runtime
by Ilona Tag
Modern data platforms have industrialized execution. We can ingest data, orchestrate pipelines, and deploy analytics platforms in days. Yet one fundamental aspect of these platforms remains largely implicit: architecture.
Today, architectural decisions are still implemented indirectly through SQL, pipelines, and tooling choices. Over time, structures emerge — but rarely as an explicit, executable system.
In this talk, I explore why modern data platforms are missing a crucial layer: an Architecture Runtime. An Architecture Runtime makes data architecture explicit, generates architectural structures deterministically from metadata, and enforces them across the platform.
Using a practical example, I show how architecture can evolve from documentation and conventions into an executable system — one that reduces drift, improves consistency, and makes platform behavior easier to govern.
Project: github.com/elevata-labs/elevata
About Ilona Tag:
lona Tag is the creator of elevata, an open-source Architecture Runtime that turns metadata into deterministic data architectures across platforms.
She focuses on data architecture, data engineering, and data modeling, with a particular interest in making architectural decisions explicit and executable.
She brings decades of experience in data warehousing and data architecture, with a long-standing focus on metadata-driven approaches.
