To wrap up this Q&A series, I thought I’d bring all the follow-up questions I’ve received under one hat. I think the aggregate of them would go something like this:
“Why is it so essential that data modelling work with multiple data sources? After all, we are talking financial securities, legal entities and so on, which everyone understands fairly well.”
Yes, on the surface, it may seem straightforward. And yes, we all understand what a financial security or a legal entity is. If you’re working with a single data provider, you might assume that “an equity is an equity” and that’d be enough. But as soon as you introduce additional providers, or even multiple platforms from the same provider, the differences quickly emerge. What appears universal at first glance turns out to be proprietary and inconsistent when you compare sources side by side.
This challenge is magnified in Fixed Income instruments, structured products, and derivatives, where schedules, attributes, and definitions vary significantly from one data source to another. Without a strong data model, aligning and reconciling these views becomes a serious uphill task.
That’s why data modelling plays such a central role in multi-sourced mastering operations. The goal is to create a true single source of truth that:
- transforms diverse proprietary representations into a consistent, standardized language;
- retains full access to the original raw and near-raw data for transparency;
- links datasets across providers with complete audit trails, so every automated or manual decision can be reproduced; and
- tracks changes in feeds and attributes in a provider-specific way without losing integrity.
This means your organization can make informed decisions based on a unified, comparable data set while still preserving all the richness and context of the underlying vendor information.
Much of the intellectual property behind GoldenSource lies in making this possible. If managing multiple providers or building a trusted ‘gold copy’ of your data is a challenge for you, we’d be happy to demonstrate how our models support that process.
In any case, I hope this brings this Q&A series to a fitting close. It really comes down to a combination of neutrality, cooperation, and robust data modelling working together to make a multi-vendor ecosystem work effectively.