Managing the Complexity of Data Management and Distribution
Cliff Cunningham and John Randles
The challenge of controlling Trade and Reference Data Management and Distribution is often underestimated. It can be a highly complex equation to manage multiple data vendors for multiple asset classes with differing identifiers and data formats, the complexity and interdependency of downstream systems and multiple trading clients with client specific trade format requirements.This paper addresses the:
- Complexity associated with Reference Data Management and Distribution
- Difficulties with Data Models and RDBMS based solutions
- Driver to turn Reference Data Management and Distribution into a competitive advantage
Highly complex all encompassing data models mapping all possible fields and relationships have been tried but with very patchy results. Point-to-point integrations of data feeds are easily created but they can quickly become un-maintainable. Business users tend to say: “Take that piece of information from there in all cases, except if it is this asset class and therefore not for these operations.” Or “It’s the same message structure as for Equities with these fields added and these other fields being populated from different sources”. This is very difficult to achieve with point-to-point integration.
The dimensions for the business rules can be arbitrary, such as client, client segment, asset type, geography, market, application version, application interface, operation type. The real challenge is to enable rules to grow in an ordered and manageable way as the complexity of your Data Management and Distribution requirements grows.
Managing The Complexity of Data Management and Distribution has been read by over five hundred executives across buy side and sell side firms. To receive a copy of this paper, please email info@polarlake.com.