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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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Data as a Product: From Collection to Control in Modern Markets
For much of the past decade, data strategy in capital markets focused on accumulation. Firms invested heavily in market data feeds, alternative datasets, data lakes, and analytics platforms. Yet despite this abundance, many organisations have still struggled to answer basic operational questions with confidence, particularly during periods of market stress. The problem is no longer...
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Data Management Summit London
Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.
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AI in Capital Markets Handbook 2026
AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...


