NYSE Euronext Client Reference Video

NYSE uses IBM Big Data solutions to innovate and prepare for the future

Published on 04-Dec-2012

Validated on 15 Jan 2014

"Big Data also provides a lot of other benefits where you can actually, if you will, mine value out of information. Currently, most people look at what happened in the past. With Big Data, it allows you to do the types of correlations to predict what’s going to happen in the future and really that’s where the business is driven from." - Emile Werr, Head of Enterprise Data Architecture, NYSE Euronext

Customer:
NYSE Euronext

Industry:
Financial Markets

Deployment country:
United States

Solution:
PureSystems, Big Data, Big Data & Analytics, Big Data & Analytics: Operations/Fraud/Threats, Smarter Computing

Overview

NYSE Euronext, a leading global operator of financial markets and a provider of innovative trading technologies, operates exchanges in the US and Europe. NYSE Euronext equities marketplaces represent one-third of equities trading worldwide

Business need:
Being a global trading and technology provider, the firm generates more than a few peta bytes (10^15 bytes) of information, every day. To remain competitive, they need to analyze both internal and external data, as quickly, efficiently and cost effectively as possible.

Solution:
Currently, IBM is partnering with NYSE Euronext to help them leverage Big Data Solutions to not only analyze, record and understand the historical data but also to innovate and foresee unique new opportunities and generate value from them

Benefits:
• Reduced the time required to run market surveillance algorithms • Decreased the number of IT resources required to support the solution • Improved ability of compliance personnel to detect suspicious patterns of trading activity and to take early investigative action, thus minimizing damage to the investing public

Video

Emile Werr, Head of Enterprise Data Architecture, talks about how the firm is taking advantage of Big Data analytics today and their plans for the future.




Video Transcript


NYSE Euronext is basically multiple companies.

It's not just the traditional trading as market, we also are in the business of selling technology. So what we do, and that expertise that we build, we are able to package and commercialize and sell back.

Our business is all about information. Data is what we live and breathe everyday. We process multi-terabytes everyday. So it's all Big Data. Everything we do is
about analyzing information, looking for a needle in a haystack. The analytics that we do is very complex.

If you don’t think big, your business is pretty much going to be dwindling down very quickly. The profit from trading is minimal. Ever since program trading
started, there is a huge number of transactions. The cost of infrastructure to support that went through the roof but at the same time the revenue being generated from that is going down.

You need to be innovative and the way you are innovative is through analyzing and mining Big Data. We see a huge business opportunity that we would help
the entire US market being able to do that type of regulation using Big Data Analytics. Big Data also provides a lot of other benefits where you can actually, if you will, mine value out of information. Currently, most people look at what happened in the past. With Big Data, it allows you to do the types of correlations to predict
what’s going to happen in the future and really that’s where the business is driven from.

By 2015, we should be able to handle 10 plus petabytes as well as being able to move tens of terabytes within an hour into and out of our systems. A centralized type of technology well integrated from a metadata perspective, well integrated from an integration perspective in terms of how users and systems interact with the Big Data system, that’s all key and we really see IBM playing a big place in that space.

Products and services used

IBM products and services that were used in this case study.

Software:
PureData System for Analytics (powered by Netezza technology)

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