In the 2011 edition of the Sybase Capital Markets Guide, Revolution Analytics CTO David Champagne talks about the need for up-to-date analytics in Finance, and how you can integrate Revolution R with quality real-time data sources. Here's an excerpt:

R represents a radically different approach to the challenges posed by analyzing increasingly large and complex data sets. Because it takes so long for traditional software vendors to update and modify their products, a new generation of analytics written in R has arisen to fill the vacuum…

Until recently, the lag time between modeling big data and deploying advanced analytics models based on it was measured in months or even years. There was simply no fast and easy way to move from the mining/modeling stageto the deployment/execution stage. But now, open source players are established at every layer: from data storage, to extract, transform and load (ETL), to predictive analytics, to deployment and presentation. Together, these components represent an “open analytics” stack: a collection of low-cost yet flexible and sophisticated tools for handling large data sets. The emergence of this technology stack is a sure sign that open source platforms are assuming more prominent roles in the expanding universe of terabyte-class analytics.

The complete article, 'Analytics R Us', can be found on pages 98-100 of the Sybase Capital Markets Guide. You can download a free copy (PDF, *reg. req.*) at the link below.

Sybase: Capital Markets Guide 2011

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