Day 1 | Main Hall - Thought Leadership and Strategic Insights

In modern systems, real-time insights aren’t a luxury—they’re a requirement. Whether you’re debugging distributed systems, tracking financial transactions, or analyzing user behavior, sub-second query latency can be the difference between reacting and proactively optimizing.
This talk dives into the technical foundations that make real-time analytics possible at scale, using ClickHouse as the case study. We’ll explore the architectural underpinnings of its high-performance columnar engine, including vectorized execution, late materialization, and how it handles time series and semi-structured data like JSON with minimal overhead.
Through real-world use cases—from high-throughput log ingestion in observability stacks, to petabyte-scale analytics for adtech, fintech, and user personalization—you’ll see how engineering teams are designing for low latency without sacrificing flexibility or scale.
If you’re a data engineer, backend developer, or platform architect working with high-velocity data, this session will give you a deeper understanding of how to build infrastructure that can keep up.

AI-driven automation is rapidly transforming data engineering workflows, from automated pipeline generation to self-healing data architectures. But does this mean traditional data engineering roles will become obsolete? This panel will debate whether AI is an enabler or a disruptor, discussing where human expertise remains irreplaceable and how engineers can adapt to stay relevant in the AI-powered future.