The bigger the number, the harder it can be to visualise. On an average day Thomson Reuters will collect a petabyte of data: that is 10 to the power of 15, or 10 with 14 more zeros.
Across our global footprint at Thomson Reuters, we distribute around 10 billion bytes of real-time pricing data every day. At its peak, as the US markets open, this can run to eight million bytes per second.
So it was with a sense of real wonder that I was able to see the US market open at the Big Bang Data art exhibition in London recently. Now touring the world, the artwork “Black Shoals Stock Market Planetarium” by the artists Lise Autogena and Joshua Portway, emu- lates a starry sky, which twinkles every time a financial transaction takes place. It brings the world’s capital flows through the major stock markets brilliantly to life.
This artwork is the largest application of Elektron Connect data anywhere in the world. More than 25,000 individual instruments are displayed in “Black Shoals,” pulling real-time data through Elektron Connect.
It is an extraordinary artwork, but also an extraordinary visualisation of the amount of data generated by just one aspect of the world’s commercial activity.
We now process and collect more data in a single day than we did in a month five years ago, with tweets, emails, PDF documents and many other formats converted into digital structures, databases and knowledge graphs. On an average day, we will collect a petabyte – that is 10 to the power of 15, or 10 with 14 more zeros.
Our greatest resource is our trusted content. And there is an enormous amount of it. For example, earlier this year our mergers and acquisitions database recorded its one-millionth entry. That’s one million M&A deals recorded on our database over the past 38 years, information we curate by scouring every source we can find from around the world and providing it to customers in the most useful way possible.
This data explosion is just one sign that we are in the midst of a Findustrial Revolution: a confluence of events – tougher regulation, massive pressure on cost, newer technologies, new platform models and thousands of technologists leaving the incumbent banks, full of ideas, money and time to disrupt the old model.
Not all companies are ready for the revolution, of course – not even those who actually utilize big data. A recent PwC survey found that some 59 percent of UK companies use data analytics mainly as a backward-looking tool to analyse previous performance. Only 24 percent used analytics to create models of future behavior. This is a significant opportunity missed.
I mentioned the scale of the data we distribute daily. What is really exciting is what we can do with it.
- We use our own predictive analytics to improve how we find, extract and tag data, enabling customers to use data in ways not possible before.
- We use semantic analysis and learning machines to generate sentiment on news and social media.
- We screen 100 million websites a day to help our customers identify hidden risks to help them protect their business.
- We have machine-learning algorithms which spot suspicious trading patterns and potential fraud, and detect problems.
And this list is, of course, by no means exhaustive. We have customers asking us to now go much further – to link our data with their data, so they can better understand where and how to invest, to discover hidden valuation and risk information, and find the risks concealed in their supply chains which can impact future performance and reputation.
One example of which I am particularly proud is our work with campaigning groups, non-governmental organisations (NGOs) and companies to develop a global information and intelligence platform, bringing together data from campaigning groups and NGOs on the ground, fully searchable, cross-referenceable and updated regularly as new reports and intelligence emerges – and available to those best placed to act on it.
Companies can gain new insight into their suppliers, identifying the weak links, bringing us a step further to cutting corrupt labour brokers from the global supply chain.
Our greatest resource is our trusted content. And there is an enormous amount of it.
The foundation of this platform we have been operating for many years, and in the last two years we have already added 48,000 entities associated with modern-day slavery. We are now broadening how we work with NGO partners and agencies to extend the information we hold.
Put simply, we are using big data to combat slavery – using new applications of technology to combat one of the world’s oldest, most terrible and most persistent ills.
It is astonishing that more than two centuries after the UK outlawed slavery that this practice can endure across the world.
Wouldn’t it be an extraordinary achievement, then, in the 21st century, to use the best in 21st century technology to track and ultimately unmask the beneficiaries of this global criminal enterprise?
Big data, when it is also open data and linked data, used intelligently and analysed for a specific purpose, can reveal extraordinary new insights into previously hidden activity. To borrow the obvious metaphor from the “Black Shoals” artwork, big data really can shine a light on the world. And that is a very BOLD idea.
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