Waters gathered leading industry experts to discuss the biggest challenges and latest developments in the big data space in a webcast on 19 April
With a growing volume and variety of data in financial institutions, firms are increasingly looking at new ways to manage and take advantage of the information to reduce risk and increase revenues. The challenge is to identify the best ways to analyze and extract useful knowledge from terabytes, or even petabytes, of data. From a technical perspective, Big Data raises a number of big challenges in terms of maximizing efficiency of the architecture and ensuring sufficient processing power for large-scale model calculations. To achieve this, firms have to consider what tools would be best for that job - given their current states.
- Consolidating data stores without giving up performance and scale that they need.
- Incorporating additional information sources to provide better context to make real-time informed decisions.
- How to make a single source of truth to bring processing to the data -- versus the data to the processing.
* Edd Patterson, Chief Technology Officer, MARKLOGIC
* Howard Halberstein, Vice President, Lead Solutions Architect - UNIX, DEUTSCHE BANK
* Dennis Smith, Managing Director, Advanced Engineering Group, BNY MELLON
* Moderator: Victor Anderson, Editor-in-Chief, WATERSTECHNOLOGY
Waters Wavelength Podcast Episode 75: An Update on the Julia Programming Language; AI & Alternative Data; Digital Currencies
Julia Computing's Viral Shah talks about the programming language he helped create and what's ahead for it. Then James and Anthony talk about the pairing of AI & alternative data, digital currencies, and Game of Thrones.Subscribe to Weekly Wrap emails
- IMD/IRD Awards 2017: All the Winners and Why they Won
- Best Market Data Provider (Vendor): FactSet
- Hall of Fame: Chris Johnson, HSBC Securities Services
- Best Evaluated Prices Service Provider: Bloomberg
- Waters Wavelength Podcast Episode 75: An Update on the Julia Programming Language; AI & Alternative Data; Digital Currencies