Buy-side firms are consistently faced with burgeoning volumes of data, necessitating adept management of expansive data extractions, a task fraught with intricacies and considerable costs. Arthur Orts ...

Quant’s David Stokes unpacks why the gap between agentic A.I. vendor promise and operational reality is widening, and why ...

Many firms are scaling their private wealth efforts without a clear understanding of where capital is truly coming from, ...

Many higher education institutions are migrating their data centers to a cloud operating model. It's a movement that has its roots over a decade ago. And while that may not be news, it's a growing ...

When the fundamentals are in place—connected systems, clear ownership and stable processes—AI can start delivering real value ...

Railpen, the fiduciary and investment manager of the UK railways’ pension schemes, has appointed BNY Mellon to provide a data operating model. BNY Mellon’s cloud-based data platform aims to deliver ...

For decades, banks have wrestled with fragmented regulatory data by investing billions in lakes, warehouses and point solutions that promised control but delivered more silos. What financial ...

If you’ve been around long enough to see a few CRM projects come and go, then you have probably noticed a pattern. Technology changes, the logos change, and the dashboards look shinier every few years ...

Taken together, these signals operationalize a data-centric oversight model. They also raise a practical question for CMC and quality leaders: if evidence is increasingly remote-ready and ...