About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

EDM is Still Relevant But DDM is Rising in Importance, Say RDR Readers

Subscribe to our newsletter

Enterprise data management (EDM) is still a relevant concept to the financial market, according to Reference Data Review’s April reader poll. However, distributed data management (DDM) is rising in importance, likely as a result of the downward pressure on costs caused by the tough economic climate and the growth of electronic trading.

According to 56% of the respondents to our reader poll, centralised data management or EDM is still top of the list for data management projects. But for 44% of respondents, distributed data models are the way forward. Last year, analyst firm Aite Group produced a report that claimed DDM was the next big thing for data management and it seems that a significant proportion of Reference Data Review readers agree. DDM extends out of the technology associated with electronic trading such as in-memory data caches, complex event processing engines, data fabrics and grid computing. The ethos behind a distributed data architecture is the creation of multiple sets of ‘truth’ where each version is unique to the subscriber and their needs. “You don’t need to house the data universe in a single instance. You can break out by geography, product type, data type, however you want to manage ‘truth’,” explained Adam Honoré, senior analyst with Aite Group and author of the report, on its release. Aite Group claimed that EDM was rarely realised in large firms due to flaws in the execution of such centralised data models. It accused such models of contributing to latency, creating a single point of failure, experiencing significant integration pain, and requiring like data be used on disparate systems. EDM projects have also frequently been criticised for involving high costs and lengthy implementation times. In an environment such as today’s, where sign off for projects is predicated on them being able to be completed within short timeframes and where budgets have been slashed to the bare minimum, EDM may be suffering due to this negative view within senior management. Although risk management and regulation have both raised the profile of data management within institutions, it could be that DDM is becoming the more attractive proposition due to its perception as a more targeted and faster approach to data management.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: In data we trust – How to ensure high quality data to power AI

Artificial intelligence is increasingly powering financial institutions’ processes and workflows, encompassing all parts of the enterprise from front-office to the back-office. As organisations seek to gain a competitive edge, they are trialling the technology in variety of ways to streamline and empower multiple use cases. Some are further than others along the path to achieving...

BLOG

SimCorp Urges a Holistic View of Buy-Side Retooling to Enable AI

You don’t have to scratch far below the surface of the artificial intelligence hype machine to see that many financial institutions are experiencing challenges in implementing the technology. Our own Data Management Insight annual preview in January of predictions for the coming year found that vendors and users alike reported the dawning of a realisation that, for...

EVENT

ESG Data & Tech Briefing London

The ESG Data & Tech Briefing will explore challenges around assembling and evaluating ESG data for reporting and the impact of regulatory measures and industry collaboration on transparency and standardisation efforts. Expert speakers will address how the evolving market infrastructure is developing and the role of new technologies and alternative data in improving insight and filling data gaps.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...