How Euronext is Utilizing Real-Time Data to Become a “Data Trader”

How Euronext is Utilizing Real-Time Data to Become a “Data Trader”

  • Martine Vesco
    Martine Vesco joined Talend in 2016 as a Senior Customer Marketing Manager. In this role, Martine develops and maintains a trusted advisor relationship with key customer contacts and creates Customer Reference programs as well as communities. Prior to Talend, Martine held a number of senior positions in customer marketing at leading software companies such as Dassault Systèmes, Business Objects and Workday.

Following its split from the New York Stock Exchange in 2014, Euronext became the first pan-European exchange in the eurozone, fusing together the stock markets of Amsterdam, Brussels, Dublin, Lisbon, and Paris.

Euronext uses Optiq, an incredible trading platform, which is the active memory of 100 TB transactions, with systems that practically work in nanoseconds. But for analytics, sometimes Euronext had to wait six to twelve hours after market close on days with important events before they could send the data to business units and clients. Also, Euronext’s storage needs continued to grow, especially following several acquisitions and with regulators, expecting that Euronext store more and more data.

Migrating to a Governed Cloud

Euronext chose Talend Big Data to absorb real-time data in an AWS data lake, including internal data from its own trading platform and external data, such as from Reuters and Bloomberg. In an ultra-regulated world, Talend Data Catalog has also proven to be highly adept at meeting the challenges of data lake governance and regulatory compliance.

"In the stock exchange sector, we follow three watchwords: integrity, because it is impossible to lose a single order; permanent availability; and governance in a highly-regulated market. Talend has met these expectations." - Abderrahmane Belarfaoui, Chief Data Officer

Making the Most of Stock Market Data

Beyond the improved architecture, the migration is also positioning Euronext to become a “data trader.” In fact, the sale of data already brings in 20% of Euronext’s revenues. Traders actually sell, buy, and make their investment decisions in milliseconds. They have a huge appetite for aggregated data in real time.

In addition to clients, this project also involves giving data scientists and business units self-service access to this data, which they can analyze in data sandboxes for tasks such as market monitoring.

Watch the full case study below:

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