Big Data: Transforming Financial IT and the Data Center

This article was written by Richard Jenkins – Senior Vice President, Global Marketing at Romonet.


‘Big data’ is a phrase that encapsulates a whole range of capital market advancements, innovations and disruptive services, including regulatory compliance, risk management, market sentiment analysis, fraud detection systems and complex algorithmic trading models.


Interestingly, these technologies are only one component of big data. Each service relies on what can be considered the foundation of our modern economic system – a global interconnected portfolio of data centers maintained by enterprises, financial exchanges, colocation operators and cloud providers. Without this IT infrastructure, international banks, trading houses and investment firms would cease to function.

Richard Jenkins


Expectedly, possessing such vast processing and data storage capabilities commands similarly large expenditures. The majority of big data-related facilities cost operators millions of dollars each year. However, despite the level of investment spent by financial organizations enhancing the functionality of their big data systems, many companies dedicate less financial resources towards an equally critical objective – understanding the data center’s true cost.


This is concerning as time is not a luxury the financial sector has. The figures associated with data centers are astonishing. The world creates 2.5 quintillion bytes of data a day (2.3 trillion gigabytes). The New York Stock Exchange collects 1 terabyte of data during each daily session. Traders are demanding increasingly complex data platforms amid periods of market volatility. Amongst all this growth, data center space must continue expanding.

Exchanging big data for lucrative opportunities


As a result, this urgency is driving a change in business models across the sector. Some financial exchanges are adapting their services beyond their core trading proposition. Borsa Istanbul and Dubai Gold & Commodities Exchange (DGCX) are showing how marketplaces are investing in their IT infrastructures and forging partnerships with colocation companies. This lets traders locate data assets as closely to the market as physically possible.


Also influencing the sector are the commercial pressures facing executives at colocation providers. Operator margins are being squeezed by an over-saturated marketplace, more mature IT buyers and hardware commoditization. Colocation companies are searching for tools capable of solving these challenges and operational models that are proven to increase financial efficiency.


Some providers are using big data analytics platforms to precisely understand customer economics. When equipped with insight into each customer’s profitability, the organization can then identify how to reduce the ratio of negative-revenue clients and stop unprofitable business practices. Within the business itself, this visibility becomes extremely powerful for the CIO and CFO who are responsible for delivering shareholder value and raising the business’s competitive position.


Furthermore, despite the colocation market predicted to reach $36 billion by the end of 2017, other operational trends can quickly influence service models. The emergence of edge computing is one compelling example.


Edge computing enables IT departments to deploy localized data hubs that are smaller in scale, simpler to manage and lower in cost. Within the context of trading, this lets financial organizations scale their data center estate sustainably, yet without the prohibitively high cost of entry typically associated with larger data facilities. This is particularly valuable for emerging markets.

The world creates 2.5 quintillion bytes of data a day (2.3 trillion gigabytes)

Ultimately, as a result many colocation providers are trying to capture the edge computing sub-sector to further grow their monthly recurring revenue (MRR) and to retain customers. Central to their business goal is big data. Much like the transformative impact that analytics platforms have already had on the buy/sell ecosystem and commercial governance, predictive modeling and cloud-based platforms are being seen by colocation providers and internal IT departments as essential revenue generators rather than IT expenses.

This trend will likely continue for some time as customers drive a change in service expectations and migrate to more demanding electronic trading strategies.               

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