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Turning commodities big data into digital gold

A man is reflected on an electronic board showing the graphs of Japan's Nikkei share average. Photography: Kim Kyung-Hoon
A man is reflected on an electronic board showing the graphs of Japan’s Nikkei share average. Photography: Kim Kyung-Hoon

Commodities big data is a precious resource, but how can companies make the most of their unstructured information to secure a knowledge advantage?


  1. Customers say the largest challenge with commodities big data is to manage and make sense of their unconnected data.
  2. Thomson Reuters has released Knowledge Graph to allow our clients to accelerate their AI and digital strategies.
  3. Being able to deeply understand the commodities ecosystem is paramount in gaining an advantage over competition.

Commodity markets are shifting at an unprecedented pace, and the volume of data that is their essence has grown exponentially over the course of the past few years.

Digital transformation is happening at different speeds in different commodities markets, but there is a growing awareness that failure to embrace digital is no longer an option.

Back in the boom times, it was not imperative for companies to deep dive into data.

But in 2008, when oil prices dropped by 75 percent in six months, something happened. In order to be able to survive, companies were forced to adopt new strategies to find alternative sources of alpha and manage risk.

What happened in 2008, and accelerated in 2014 when oil prices dropped by 60 percent over less than five months, is that companies started investing heavily in technology and digitalization.

Supply and demand imbalances

Compared with other asset classes, commodities have a physical dimension.

Supply chains are based on the assumption that physical commodities will be of a specified quality and quantity, and that they will be delivered from one point to another within a specified time frame.

Part of this uncertainty can be reduced by having full line of sight on the global production of a given commodity and a detailed understanding of the current, and projected, supply and demand imbalances.

Commodities YTD selected asset performance. Turning commodities big data into digital gold

study from McKinsey & Company found that despite the fact that 90 percent of all digital data has been created in the past few years, only 1 percent of it has been analyzed.

The exponential growth the Internet of Things (IoT) is contributing has transformed this information overload into a commodities data tsunami.

Unconnected data

Commodities companies have been using sensors for years, but as these sensors are now connected to the internet, their data flow can enable real-time analysis on a global basis.

However, it is not a negligible task to normalize the numerous internal and external data sources that define global commodities supply chains, and then analyze the resulting massive information flow in order to extract useful, timely, and actionable insights.

Learn how Thomson Reuters Commodity Market Solutions provides comprehensive coverage of the commodity markets

Many of our customers say that the largest challenge they face with commodities big data is to manage and make sense of their unconnected data.

We have been successful in doing the heavy lifting of organizing and connecting of companies’ internal and external data, so they can concentrate on the insights generated and focus on delivering benefits to their business.

Smarter humans with smarter machines – the journey. Turning commodities big data into digital gold

Knowledge Graph benefits

Apart from our own platform, our enterprise data management solution allows clients to seamlessly integrate their proprietary data with that of Thomson Reuters and other third-party data sets.

This unique collaboration is designed to allow commodities big data from any number of providers to be stored in one single place.

What our clients are also telling us is that the quest for sourcing alpha is transitioning away from traditional structured data to unstructured data.

To turn this large amount of unstructured data into a precise advantage, we are the first major information provider to release a Knowledge Graph to allow our clients to accelerate their AI and digital strategies.

Example of a Knowledge Graph. Turning commodities big data into digital gold
Knowledge Graph example

A representation of the relationships across all enterprise data, knowledge graphs use natural language processing, AI, text analytics, and data-mining technologies to tag people, locations, facts, and events to enable companies to understand the ecosystem in which they live.

Competitive advantage

I am often asked, “What is the most valuable commodity?” It is knowledge.

Being able to deeply understand the commodities ecosystem is paramount in gaining an advantage over the competition.

Commodities companies able to assimilate this information tsunami, understand it, and act upon it with confidence, will be the ones that will emerge as the future leaders.

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