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Big data

The necessity of human touch in machine learning

Mona Vernon  Chief Technology Officer, Thomson Reuters Labs

Mona Vernon  Chief Technology Officer, Thomson Reuters Labs

The volumes of data generated every day won't reveal anything in and of themselves. Human expertise is needed to make sense of them.

Industries across the world are more connected than ever. Companies that operate internationally are reliant on a wider sphere of influencers, providers and partners. All of these relationships create the potential for business insight, but how do you tap into that data?

For example, could a story about a commodities shortage in one region and the cancellation of vehicle orders from one company be linked? Beyond that, could this action potentially impact other at-risk entities that are not immediately apparent?

Graphing – building a relationship ecosystem between sets of data – is one approach we can take to unlocking this information: These links, between people, organizations and other key metadata, can reveal new insights and provide access to unforeseen data.

“This journey needs to start with a human touch, from people who understand Big Data in the context of the industries our customers operate in”

A data ecosystem

Some organizations are doing this at small scale with singular, isolated data sets. Thomson Reuters is uniquely positioned to unlock the possibilities at a much greater scale. We have data from over 35,000 sources and from hundreds of unique partners. Moreover, every day we are sharing knowledge with customers, academics and start-ups to co-create new solutions driven by these data sets.

Globally, 1,800 terabytes of data are created every single minute. While the sheer magnitude alone may be intimidating to some, I see this as 1,800 terabytes of opportunity.

The challenge in bringing together multiple data sets is a lack of commonality. This is where human expertise is vital in quantifying the right parameters. Standardization is necessary to be able to extract the right answers to solve global challenges.

Data visualization can make clear previously unobserved connections.
Data visualization can make clear previously unobserved connections.

The human touch

Perhaps more important than the data are the human experts who can engineer that data in ways that add layers of value. Linking it to relevant content and building relationships, for instance, or tagging it with advanced, detailed metadata to give information an identifiable permanence wherever it occurs – these are the sorts of things for which human input is needed.

Using artificial intelligence, machine learning or clustering with some large data sets will only get you part of the way. This journey needs to start with a human touch, from people who understand Big Data in the context of the industries our customers operate in, and who have a proven track record of tackling data-driven problems to help businesses find new opportunities.

Evolving how to find Trusted Answers

Bringing together vast amounts of data, human expertise and curated technology, you can find what you need  – or maybe even what you didn’t know you needed.

To pull together these three sources of information, we developed Thomson Reuters Knowledge Graph Feed, the first and largest relationship graph of its kind for financial services. The graph provides a trusted data source and model for customers to leverage, build their enterprise solutions on top of and benefit in new, connected ways from the breadth of the Thomson Reuters open platform.

“The Knowledge Graph enables financial firms to understand the complete picture of the financial ecosystem.”

Our trusted reputation with handling market and sensitive content makes us the perfect partner to transparently explore the relationships between linked data. Knowledge graphs like these are the ecosystems that highlight meaning from previously unknown connections.

With Knowledge Graph Feed, we identify over 2 billion of these relationships. Building a solution powered by the feed would show customers how that earlier commodities shortage and cancellation of vehicle orders were related. A structure like this in the Knowledge Graph enables firms to understand the complete picture of the financial ecosystem, thus helping to de-risk their portfolios and mitigate crisis before it strikes.

This is just one way that Thomson Reuters Labs is working with our businesses to provide our customers with the unparalleled knowledge they need to be successful. This is an exciting evolution in how we are utilizing emerging technologies and data to drive deeper insights for our customers, helping them find trusted answers in this ever increasingly complex world.


Learn more

Visit Innovation @ ThomsonReuters.com to learn more about how we are pairing technology with human expertise at Thomson Reuters Labs™.

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