Data Council is heading back to the Bay. Join us April 22nd - 24th, 2025, for three days of no-nonsense, data-driven discussions in the SF Bay Area. Expect to dive deep with over a thousand attendees and speakers from top data teams across hyper-scalers, startups, and industries like tech, finance, media, healthcare, and more.

If you’ve got insights on data infrastructure, AI and ML tooling, storage systems, AI engineering, analytical processing, data science models, applied AI, computer vision, OSS data tools, building strong data cultures, or any cutting-edge technical data topic, we want to hear it.

Submit your talk ideas by November 15th! Don't miss the chance to add your voice to the mix.

Learn about Data Council

Event Dates: April 22 - 24, 2025
Location: SF Bay Area (IRL only)
Presentation Time: 30 minute talk + 5 minutes of Q&A

What We Look For in Talks:

• Deep Technical Depth: We're looking for talks that dive into the latest advancements from a technical perspective. Bring your expertise from the cutting edge.
• Real-World Challenges and Solutions: Share stories of overcoming complex challenges in building data platforms and products at your company. We’re interested in real-world applications, case studies and real examples of systems you've built. 
• Innovative System Design: We value fresh, hands-on approaches to system design, especially when paired with thoughtful discussions on architectural tradeoffs. Share your unique methods and insights for building robust systems.
• Evaluation Criteria: Talks are judged on technical depth, the speaker’s experience, and their potential appeal to our audience. 
• Vendor Participation: Vendors are welcome, but should put forward an engineer to discuss how their tool or product was built—focus on the ‘how,’ not just the ‘what’ or a usage tutorial. (For sponsored workshop opportunities, please contact community@datacouncil.ai.)

Our 2025 Tracks:

• Data Engineering & Infra: covers modern data workflows, storage systems, and design patterns, focusing on key pipeline components like data-ops, data quality, ingest, ETL/ELT, monitoring, metadata and streaming.
• AI Engineering: goes deep on the skills and toolchain every AI engineer must know to build, deploy and scale AI systems. Example topics covered include model selection & evaluation, RAG, vector & graph search, fine-tuning, agent orchestration, data prep and testing/deployment/monitoring.
• Data Science & Algos: covers useful algorithms, modern research and frameworks & methodologies relevant to data science roles.
• Applied GenAI: dives into the practical application of GenAI across industries. We discuss how orgs can innovate in content creation, automation, customer engagement, and product development. Hear real-world case studies of AI architectures, best practices for integrating GenAI into existing workflows and the ethical considerations surrounding its use.
• Analytics & BI: covers tools and techniques for data analysts, including BI, customer analytics, A/B testing and data visualization.
• Foundation Models: focuses on the rapidly evolving landscape of foundation models, such as large-scale language models, multimodal models, and AI systems that serve as the backbone for a wide range of AI applications.
• MLOps & Platforms: explores the engineering of machine learning systems, frameworks and tools, covering data preparation, feature engineering, model quality and monitoring.
• Databases:  dives into the evolving world of databases, covering both traditional relational systems and emerging database technologies designed to handle the complexities of modern & unstructured data.
• Data Culture: features insights on building vibrant, cross-functional and collaborative teams and how data teams can function best within larger organizations.
• Lightning Talks: 15-minute, bite-sized sessions from startups sharing lessons and best practices from their rapid growth.
  

Why Speak at Data Council?

Need Inspiration?
Watch previous years' talks on our YouTube