As both a producer and consumer of vast amounts of information, Thomson Reuters needed a centralized cloud-based repository of information to provide a single source of truth on corporate data.
Carter Cousineau, Vice-President of Data and Model Governance at Thomson Reuters, explains:
I think, for many organizations, it becomes difficult to determine which data warehouse and data platform you'd want to utilize and to find the one that works for your organisation. But broadly speaking, you need to nail that strategy first and foremost around your data analytics and AI model – and then, if you make the right choice, the tools will support the other work your team wants to do.
To that end, Thomson Reuters has developed a data strategy that aims to transform business processes through heavy use of cloud-based services. The objective is to give producers and consumers of data greater visibility and to create an easy-to-use platform that allows staff to dip into data safely as they create new insights. Cousineau says:
We're into year three of that journey now. Our efforts to make more progress on the data strategy relate to the time and bandwidth our teams have to be able to move the data effectively, so that it's ready for consumption. But the goal is to transition the data platform to self-service and support faster consumption on a secure environment.
All enterprise information now goes into a Snowflake Data Cloud and is stored in Thomson Reuters’ Data Platform, she adds: .
We’ve built it in a way that will support a lot of the data sources that are now being used. We have a variety of sources already in the platform, whether that’s marketing, finance or risk data – and we're expecting that to continue growing.
Providing new levels of data visibility
The next stage of work involves moving all customer experience information to the Snowflake Data Cloud. This transition will provide employees with a full perspective of the company’s data and give staff the potential to develop deeper, cross-organization insights, according to Cousineau:
For any information that lands in the data platform, we work on ensuring it's governed. We have different tools in place to help support automation of security and access features, classification of data, and data lineage.
Thomson Reuters leveraged Snowflake’s security architecture, along with Immuta’s data security platform, to deploy new data workloads to the cloud safely and effectively. Cousineau says this integrated approach to security is one of the key things that continues to make the Snowflake platform appealing. As professionals across the business use data operationally, they have full visibility into who created information and how it’s being used:
It’s not just the producer view, but who else is using your data. And then, as you're working through your tasks, the platform ensures consumers get the appropriate access and security requests that go back to the data owner.
Cousineau says any effort to centralize data comes with challenges. While technical obstacles can be overcome, she advises that digital leaders should pay attention to cultural concerns, particularly any issues that arise due to the introduction of a new, cloud-based ways of working:
You need to ensure you have that joint alignment at the forefront and remove some of the barriers, so people know that using this new technology platform makes sense. Snowflake is a secure environment for data – and it’s been proven that it’s better putting information in the cloud than not moving to the data platform.
Looking to embrace AI
As Thomson Reuters looks further ahead, AI is on the agenda. Cousineau hopes such advances will help Thomson Reuters serve its clients effectively in the future:
We pride ourselves in being a trusted organisation that provides trusted content. I'm very interested in their work in the generative AI space and looking to see how it's going to unfold.
Like other blue-chip enterprises, Thomson Reuters is just starting to explore the potential of these emerging technologies, especially generative AI. She says her own firm is still at the nascent stage of implementation but there’s a lot of interest around how use cases might develop:
Those explorations are probably changing daily and I'm curious to see – not just at Thomson Reuters, but generally – what will stick for certain organizations and what will work for their customers. We're looking at it around the opportunities for creating innovation, and then building off some of the products that we already have in place, and how could we better optimise and create value. There's a world where we can push the conversational aspects of AI further into products, but developments are changing really, really rapidly out there in the market.