Day 1 | Main Hall - Thought Leadership and Strategic Insights

In an era where financial decisions hinge on millisecond precision, delivering real-time price streams to end-users is no longer a luxury — it’s a necessity. This talk explores modern best practices in building low-latency, highly reliable real-time data pipelines using technologies like WebSockets and NATS. We’ll dive into the architectural patterns that enable microservices to stream live pricing data seamlessly, and how tracking end-to-end latencies — from client browsers to backend systems — is both crucial and challenging.
Learn how these real-time streams not only power live charts and dashboards but also feed AI systems that detect anomalies, forecast trends, and trigger intelligent actions. If you’re building platforms where speed, scale, and accuracy are non-negotiable, this session will offer practical insights and proven techniques to get it right.

In today’s data-driven world, context is everything. Without context, raw data can often lead to inaccurate insights, misinterpretations, and missed opportunities. For data engineers, this means building platforms that enrich data with relevant business context and provide strategic insights.

Join this session to explore how modern, context-centric platforms help businesses stay ahead in the data-driven landscape.

As organizations race to adopt Generative AI, a strong and scalable data foundation is essential. This session explores how building a FAIR-aligned Data Marketplace has transformed data access, quality, and governance- paving the way for AI-driven innovation. Learn how a persona-driven, self-service platform powered by Snowflake, Power BI, and advanced metadata cataloging accelerated decision-making, eliminated redundancy, and boosted adoption by 25%. Key innovations include a real-time Data Quality Index, seamless integration for both technical and non-technical users, and smart search capabilities using LLMs. Discover how strategic leadership, automation, and a culture of collaboration are driving enterprise-wide data democratization- preparing the organization to fully harness the power of Generative AI.

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.