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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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12 Companies Bridging Agentic AI and Data Management in Capital Markets

The friction inherent in mobilising data is a perennial problem for financial institutions, who have spent the last decade perfecting the passive data stack – investing heavily in cloud warehouses, governance frameworks and ETL pipelines designed to move data for human consumption. However, the operational reality remains plagued by manual intervention. Recent developments in agentic...

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AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

Regulatory Data Handbook 2026 – Fourteenth Edition

Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...