Gaining value from data through science and engineering

How much time do data scientists, analysts and quants spend doing the jobs they're employed to do? In the vast majority of cases, not enough

The Panel

  • Carl Reed, Global Head of Data License Product, Bloomberg
  • Michael Atkin, Strategic Advisor, EDM Council
  • David Saul, Senior Vice-President and Chief Scientist, State Street
  • Rick Aiere, Project Management Professional, Customer Service Manager, Senior Enterprise Architect, AIG
  • Moderator: Max Bowie, Editor, Inside Data Management

Data is a firm’s most valuable asset, but equally important are data experts who turn data into strategies and actions. However, as data budgets are consumed by regulatory compliance initiatives, the potential of this data is frequently compromised.

Instead of concentrating on leveraging data as a competitive differentiator, these expensive resources often find themselves under-utilized, spending the majority of their time performing data engineering and lengthy processing tasks, rather than focusing on analysis and data strategy. To take full advantage of their existing investments in data and staff, firms are looking for better ways to execute their common enterprise data engineering requirements, including by building partnerships with key data suppliers. 

A panel of experts discusses how firms can benefit from enlisting data suppliers to perform the heavy lifting of data pre-engineering, allowing staff to work more efficiently.

Key topics discussed include:

  • Laying the foundation for improving competitive edge through accurate and consistent enterprise data management
  • Leveraging investments to enable new user types to create proprietary signals that deliver a trading advantage
  • Identifying the right data partner to provide core data, context and quality
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