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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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Dakota Q&A: From Fund Raiser to Private Market Data Specialist
Two decades since its formation, Dakota has transformed its business from raising capital to providing private market participants with data and tech services. It’s history is one of nimble adaptation and being able to divine the growing needs of a booming yet often opaque corner of the financial sector. Company President Rob Robertson spoke to...
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AI in Data Management Summit New York City
Now in its second year, the AI in Data Management Summit NYC explores what changes when AI becomes part of the data management operating model.
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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...


