How Unified Infrastructure Supports Modern Capital Markets Workloads
Capital markets teams are processing more data across longer trading hours. They also face shorter research cycles and growing demand for real-time and AI-driven analysis. Many firms rely on separate tools for ingestion, storage, analysis, and visualization. Each handoff adds operational complexity and can introduce duplicated data, inconsistent results, and slower queries.
In this on-demand webinar, KX experts discuss the requirements for a unified trading data platform. The panel covers how firms can plan for higher data volumes, run research and backtests faster, and support real-time and AI workloads.
You’ll also hear how KDB-X supports streaming, historical, and vector workloads in one runtime. The panel explains how teams can query structured, unstructured, and time-series data with q, Python, or SQL, while retaining control over data access and AI workflows.
What You’ll Learn
- How market and regulatory changes affect data volumes and infrastructure planning
- Where fragmented systems add cost, complexity, latency, and data duplication
- Which capabilities support real-time, historical, and AI workloads
- How unified data access can shorten research and backtesting cycles
- How KDB-X supports analytics across time-series and vector data
- How governance and guardrails control access to data used by AI systems
Who Should Watch
This webinar is for people who shape trading data and analytics decisions, including leaders and practitioners in platform engineering, trading technology, quantitative research, data, risk, and surveillance.
Speakers
- Patrick Carroll, Account Executive, KX
- Alex Weinrich, Solutions Engineer, KX
- Nicolas Khouri, Product Manager, KX
- Dan Tovey, Host, KX