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

Deutsche Bank’s Walker Expounds on the Benefits of an MDM Warehouse

Subscribe to our newsletter

When it comes to the rather “unsexy” problem of tackling a firm’s master data challenges and ensuring that as much point to point architecture has been eliminated as possible, there is nothing better than a master data management (MDM) warehouse, said Shannon Walker, business architect for Finance Change at Deutsche Bank, to delegates at this month’s TSAM. Walker, who prior to her role at Deutsche was also a data architect at Aviva Investors and Citigroup, discussed her current firm’s decision to establish three golden sources for its master data in order for it to be exposed to scrutiny by analysts in a centralised manner.

The reason behind the decision to have three golden sources (as opposed to just one) was driven by downstream user requirements, said Walker. On this note, at last year’s TSAM, she spoke about the need to involve downstream users from the business in data management projects in order to ensure they are on board with the changes, which she again reiterated this year. Building consensus for the launch of a project is easier from the grassroots level of those that have to deal with the data on a daily basis because they appreciate the challenges involved, she said. Hence the decision to support these downstream requirements with three specifically formatted golden sources; one size does not fit all.

Walker elaborated on the challenge of agreeing the terminology within a firm with regards to master data due to the range of different uses for reference data, depending on the function of the downstream users involved. Once this has been tackled, the benefits of MDM are obvious, she said: “Consistency and transparency of data, as well as reusability of that data across an organisation and the obvious benefit of cost reduction.”

From an IT perspective, the centralisation of this master data means that new solutions such as front office tools can be plugged into the correct data feeds and get up and running much quicker, she added. The MDM middleware therefore decouples the business changes from the technology changes, thus allowing one to be altered without dramatically impacting the other.

The nature of the challenge also means that those involved in the data management function need to be both experts in technology and individuals well versed in the requirements of the business, noted Walker. “They need the expertise to talk data and the business language to be able to reflect the organisation’s goals. Making the benefits clear to the business is a key job, such as highlighting the increased accuracy of the numbers for external clients,” she explained.

However, one particular language problem raised by the delegation was that the very definition of what constitutes master data is open to interpretation. Walker indicated that this is where semantics comes into play, so that all parties are able to understand the basic tenets of master data, which she defines as fundamental and global in nature, versus more general reference data.

She also warned that data management teams should not get “hung up” on governance, but should put in place various incentives and penalties to encourage a more data focused culture around specified procedures and data stewardships. The three tenets of this lie around semantics, ownership and integration, she explained, “from that point, you can begin to chip away at the iceberg”.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Are you making the most of the business-critical structured data stored in your mainframes?

Fewer than 30% of companies think that they can fully tap into their mainframe data even though complete, accurate and real-time data is key to business decision-making, compliance, modernisation and innovation. For many in financial markets, integrating data across the enterprise and making it available and actionable to everyone who needs it is extremely difficult....

BLOG

Being Prepared for Tomorrow Requires an Advanced Data Architecture Today

By Don Huff, Global Head of Client Services and Operations, Bloomberg and Maureen Gallagher, Head of Enterprise Reference Data, Bloomberg. Data has quickly become the hottest commodity in the financial sector: trading and investment teams are laser-focused on accessing the best, newest data to get an edge on the competition. While this arms race for...

EVENT

TradingTech Briefing New York

Our TradingTech Briefing in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

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...