Open source is at the heart of the modern data lakehouse, shaping how organisations achieve flexibility, interoperability, and performance at scale. This panel brings together leading community members from Apache Iceberg, Apache Arrow, and Apache Polaris to explore the present and future of Lakehouse OSS. Panelists will discuss how these projects are evolving, the challenges they’re addressing, and the opportunities they unlock for building truly open architectures. Join us for an engaging conversation on how open source innovation continues to push the boundaries of what’s possible in data platforms.

Enterprises are moving beyond AI experiments and copilots for individual productivity toward the next stage: the Agentic Enterprise, where AI agents drive insights, decisions, and workflows at scale. In this session, Rahim Bohjani, CTO of Dremio, will outline the enterprise AI maturity journey and show why most organizations are still stuck between prototypes and production outcomes. Through live demos and real-world use cases, you will see how Dremio’s open lakehouse platform provides the intelligent data foundation needed to advance. It delivers semantic consistency, zero ETL federation, autonomous optimization, and built-in governance. Learn how organizations can progress from isolated AI pilots to enterprise-wide impact, and why rethinking data architecture is essential for making AI deliver real business value.

Trusted Data Solutions in sensitive industries such as healthcare and the public sector must combine sovereignty, compliance, and scalability with the ability to integrate diverse data sources.
Danyel Gros and Marcel Just from STACKIT will share insights into how the sovereign cloud foundation of STACKIT and the open lakehouse platform of Dremio work together to provide consistent access, built-in governance, and efficient data management without heavy integration overhead.
This combination will be illustrated through the example of a Medical Data Platform, showing how sensitive information can be managed securely while enabling a scalable and future-proof data foundation for research and healthcare services.

In this session, DATEV outlines their data landscape and discuss pre-Dremio challenges. They showcase their current self-service analytics process using Dremio, detailing their technical infrastructure.

Ever felt like accessing production data requires a secret handshake with IT – and maybe some cookies? At Schaeffler, our data scientists decided it’s time to break the cycle. In this session, we’ll share how we’re using Dremio to make large-scale production data AVAILABLE TO ALL – no magic spells or endless helpdesk tickets required.

We’ll take you through:
The not-always-easy journey from “Can I have that dataset, please?” to true data democratization
Two real-world use cases that sparked our transformation, including our motivations and guiding principles
What it looks like behind the curtain
Where we’re heading next – AI, chatbots, and whatever disruptions come our way!

This talk takes you on a journey through the evolution of data transformation—from traditional rollout processes rooted in data warehouses, to modern, automated workflows designed for the lakehouse. We’ll explore practical approaches using Dremio and declarative frameworks like dbt, highlighting how teams can transition toward scalable, maintainable solutions. The session concludes with a look at Agentic AI: what’s already possible today, and where intelligent automation might take us next.

The Challenge

Granicus (14 acquisitions, 5 countries) struggled with fragmented government data across 14+ sources: Salesforce CRM, EHQ MySQL, Matomo streams, GovD Oracle, Open Cities scraping, and more. Needed unified citizen analytics with regulatory compliance.

Technical Solution

– Nessie Catalog + Generative AI
– Iceberg metadata format with AWS S3 auto-reflections
– OpenSearch knowledge base for context-aware AI responses
Advanced Semantic Layers

– Complex multi-domain models with automated reflection optimization
– Query times: minutes → milliseconds through intelligent materialization
Dremio MCP NLP-to-SQL

– “Show housing meetings with >100 attendees last quarter” → Instant SQL
– Government-trained language models with optimal query generation
Dashboard Architecture

– Highcharts integration via Dremio REST APIs
– Intelligent caching for sub-second UI responses
– Real-time citizen engagement metrics
Zero-Copy Pipeline

– 14+ sources unified without data movement
Live Demos:

– NLP query: “Find legislation about housing with citizen feedback >8”
– Real-time reflections optimization
– Highcharts dashboard with live government KPIs
– REST API caching performance comparison
Results:

– 95% faster time-to-insight
– 60% cost reduction through reflections
– 300% increase in self-service adoption
Takeaways:

– Nessie + Iceberg configuration guide
– NLP-to-SQL with Dremio MCPs
– Highcharts-REST API integration patterns
– Reflections optimization playbook
Experience instant citizen insights through plain English queries powered by Dremio’s zero-copy architecture and intelligent semantic optimization.

As organizations adopt AI at scale, managing data governance becomes crucial to ensure trust, compliance, and security. In this session, we will explore how Dremio enables governance in the AI era by providing a unified, secure, and high performance data platform. Learn how to implement policies that ensure data quality, maintain lineage, and enforce access controls while empowering data teams to deliver AI insights faster. Whether you are building AI models or deploying analytics across the enterprise, discover practical strategies for governing your data without slowing innovation.

Unlock the power of open data! Explore how Iceberg’s REST spec and Polaris enable seamless interoperability across your data ecosystem. Connect tools, share insights, and keep your analytics flowing—open, flexible, and friction-free.

Open source is at the heart of the modern data lakehouse, shaping how organizations achieve flexibility, interoperability, and performance at scale. This panel brings together leading community members from Apache Iceberg, Apache Arrow, and Apache Polaris to explore the present and future of Lakehouse OSS. Panelists will discuss how these projects are evolving, the challenges they’re addressing, and the opportunities they unlock for building truly open architectures. Join us for an engaging conversation on how open source innovation continues to push the boundaries of what’s possible in data platforms.