Market data serves as the foundation for financial services. However, for many organizations, technical limitations have created significant fragmentation, operating issues and high costs when ingesting and transforming market data – and in particular tick data – across the front, middle, and back office. This has resulted in inefficiencies with use cases ranging from quant research and alpha generation to risk analytics and regulatory reporting.
But with technological advancements made because of generative AI, organizations can now rethink how they approach their market data strategy. Capabilities, including vectorization, can now be leveraged to more easily aggregate timestamp data without separate specialized vector databases.
Join this session to learn how data leaders and market data teams should be thinking about their enterprise market data strategy in a way that streamlines data access, but also reduces TCO. In this webinar, we will:
- Share best practices for how organizations should think about and future-proof their market data estate
- Deep dive into new time series functionalities, including a live Snowflake demo for vector functions to enhance tick data processing using with cutting-edge AI and ML techniques
- Explore how Snowflake Marketplace and Snowflake Native Applications easily facilitate improved tick and market data sharing and analysis
Speakers
Chris Napoli
Head of Asset & Wealth Management
Snowflake
Bryan Lenker
Global Financial Services CTO
Snowflake
Anand Pandya
Global Head of Financial Services
Hakkoda
Register Here