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For example, the International Securities Exchange, which has just received approval from the US Securities and Exchange Commission to charge fees for its low-latency direct feed of market depth data, is also expanding the analytics available on its PrecISE front-end trading application with the addition of greek values.

Even those whose main interest is in low-latency data still recognize the value of analytics and deeper metrics. For example, trading system vendor Sterling Trader, which is using technology from Chicago-based SpryWare to capture low-latency data from European exchanges and multilateral trading facilities, also asked the vendor to create additional metrics and index values to augment the raw data.

Meanwhile, pure analytics providers such as Houston, Texas-based Aqumin are also seeing interest in their products. Aqumin analyzes different data factors using heatmap displays that the vendor says are more intuitive than lists of numerical values. Chief executive Michael Zeitlin says that since life conditions us to recognize visual patterns between objects for everything that we do, using graphics to visualize data comes naturally, and enables users to spot potentially profitable movements quicker and easier.

But some believe that new, evolving types of analytics need more attention. "There has been a significant focus on charting. We now have very good ways to visualize time series, but very few good ways of understanding when a market event is truly significant," says Kerr Hatrick, head of quantitative products, One, Asia, at Deutsche Bank.

In the Analytics report, Capital IQ's chief technology officer William Murphy describes the vendor's evolution from an equities-driven platform for investment bankers and M&A professionals to one that integrates qualitative and quantitative data and models for screening, back-testing and return attribution. "The marriage of sophisticated quant tools and best-of-breed fundamental data has spawned a new age of ‘Quantamentals' [for] analyzing large amounts of data," Murphy says.

Participants in our Q&A say the next generation of analytics will not only leverage new technologies, but also new sources of data to expand productivity and knowledge. These could increasingly incorporate Internet content, which the new generation of investment professionals are more comfortable with and savvy about than their predecessors, as well as monitoring and triggering capabilities that can adjust models and cross-reference against a range of multiple datasets, which can contribute directly to automated trading systems.

In the future, analytics may be incorporated into algorithmic trading systems, and the data inputs on a company may be the Twitter feeds of its employees. And while desktop displays aren't likely to disappear, the traders of the future are increasingly automated applications. So for that new consu-mer base, the technologies that establish causal connections between data-added-value CEP, if you will-may be the new wave of analysis tools.