Open Lakehouse + AI Mini Summit | Mountain View
- Date
- 2025-11-13
- Location
- Mountain View, CA, USA
- Host
- Open Lakehouse + AI
About this event
The open lakehouse and AI stack is moving fast, and the people building with it need more than broad trend talk. This mini summit in Mountain View is designed for practitioners, technical leaders, and curious builders who want a sharper understanding of where open data platforms, table formats, and AI systems are headed — and how those pieces fit together in real environments. About the Event This is an in-person mini summit focused on the intersection of AI, open lakehouse architecture, and the technologies shaping modern data foundations, including Delta Lake and Iceberg. If you care about how data is stored, managed, governed, and made usable for intelligent systems, this event is built to give you relevant conversations and practical perspective. Rather than trying to cover everything at a high level, the event centers on a focused set of themes: open table formats, interoperable data infrastructure, autonomy, and the community shaping these tools in practice. Expect a format that feels more concentrated than a large conference and more cross-functional than a narrowly technical meetup. Because it is a mini summit, the value is in the density: a shorter, more intentional gathering where the signal stays high. You can spend time on the ideas that matter right now without committing to a full multi-day event. What to Expect You should expect a mix of talks, discussion, and community interaction anchored in the realities of modern data and AI systems. The event themes suggest a program that connects foundational infrastructure questions with applied AI use cases, so attendees can think across the stack rather than in silos. Topics likely to frame the day include: Open lakehouse architecture and why it matters for flexibility, scale, and long-term platform choices Delta Lake and Iceberg as important parts of the conversation around open data formats and interoperability AI workloads and what they require from data infrastructure in terms of reliability, freshness, access, and governance Autonomy as an emerging area, including how intelligent systems depend on strong data foundations Community-led learning from people evaluating, adopting, or building in this ecosystem Because the event is in person, a key part of the experience will be the room itself: side conversations, live questions, and the chance to compare approaches with others solving similar problems. Whether you are deep in architecture decisions or just beginning to evaluate the open lakehouse landscape, those interactions are often where abstract concepts become usable. You can also expect a pace that respects attendees' time. A mini summit format usually works best when sessions are focused, transitions are efficient, and there is enough room for meaningful networking without the sprawl of a much larger event. Why Attend If your work touches data platforms, analytics, machine learning, or AI product development, this event offers a chance to connect the big picture to operational decisions. The lakehouse conversation is no longer just about storage formats or pipeline design; it increasingly affects how teams support experimentation, production AI, governance, and future platform flexibility. Attending can help you clarify questions such as: What does an open data architecture actually enable in practice? How should teams think about Delta Lake, Iceberg, and ecosystem compatibility? What kind of data foundation is needed to support AI systems that are dependable and scalable? Where is the space heading, and what assumptions are worth revisiting now? There is also value in hearing how others are thinking through tradeoffs. Many teams are balancing performance, openness, cost, developer experience, and organizational complexity all at once. A focused summit creates a good environment for comparing notes with peers who understand those pressures. Just as important, this is a community-centered event. That means it is not only about absorbing information; it is also about meeting the people shaping the conversation, asking better questions, and building context you can take back to your team. Practical Details The event takes place in person in Mountain View, USA on Thursday, November 13 at 12:00 PM PST. If you prefer real conversations over virtual panels and want the benefits of being physically in the room, this format is a strong fit. A midday start makes this a practical option for local attendees, Bay Area teams, and anyone planning around a workday schedule. It is well suited to people who want a concentrated learning and networking window without needing to block off several days. A few reasons the in-person setup matters: You can ask nuanced questions in real time You can meet others working on similar architecture or AI challenges You can build relationships that are harder to create online You can leave with a clearer sense of the people, priorities, and momentum in this space If you are actively evaluating open data strategies, building AI-enabled systems, or simply trying to stay current on where the open lakehouse ecosystem is going, this mini summit is a timely reason to step out of your inbox and into the conversation.
Who should attend
If you're working at the intersection of data infrastructure, analytics, and AI, this will likely feel highly relevant. - You are a **data engineer, platform engineer, or architect** thinking through lakehouse design, table formats, interoperability, or long-term platform choices. - You work in **AI or machine learning** and want to better understand the data layer that supports reliable training, retrieval, evaluation, and production workflows. - You lead or influence **technical strategy** and need a clearer view of how open ecosystems like Delta Lake and Iceberg fit into future-facing data decisions. - You are building products or internal systems involving **autonomy** and want practical context on the infrastructure these systems depend on. - You value **community-driven learning** and want to talk with peers, compare approaches, and hear how others are navigating similar tradeoffs. - You are curious about the open lakehouse space but want something more focused and useful than a broad, high-level conference. If you want grounded conversations about where open data architecture and AI are meeting right now, this is the right room.