Take a look at the highlights from our Spring Data Management Summit in London.
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The democratisation of data has encouraged engineers to think about how to make their data estates more accessible and useable for non-technical business end-users. Translating intention into data action requires careful configuration that enables consumers to mine insight, analytics and value without having to use precise technical terminology. Data engineers achieve this through semantic layers,...
The high level of data and data product use-case customisation among financial institutions offers an insight into the challenges that technology teams face in managing their organisations’ data. Observability has become more difficult as each data user tailors their tech provisions to their own business needs and data provisioning must be similarly responsive at a...
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.
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...