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Recorded Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research
For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...
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AI in Finance Requires Developing the Right Operational Mindset
By Carl Thornberg, Head of Optimisation and Analytics Technology at OSTTRA. Integrating AI into the finance sector requires navigating a robust regulatory landscape designed to ensure stability and security, a process that demands a deliberate and meticulous approach to technology adoption. To build confidence for experimentation with this not-yet-fully-understood technology, essential safety nets must be...
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Data Management Summit London
Now in its 17th year, Data Management Summit (DMS) London returns In April 2027, to explore how to use data and AI to drive measurable business outcomes reliably, repeatedly and at scale.
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Alternative Data in Capital Markets Handbook 2026
Alternative data adoption in capital markets has moved into a more disciplined phase. Simply possessing a dataset is no longer a differentiator – the priority now is how data is sourced, synthesised and deployed, and how quickly granular, disaggregated signals can be turned into validated, decision-ready insight. The 2026 edition of the Alternative Data in...


