Despite the fact that many are still uncomfortable with the term “big data,” the impact it has had on an increasingly diversified and electronic financial services industry is incontrovertible. Other industries already employ big-data analytics to support a variety of functions, and while capital markets firms have been relatively slow to realize the potential benefits of sifting through the vast amounts of data they generate, technologies such as Datawatch Desktop have become an essential part of the buy-side toolkit. It’s not just a “nice to have”—a tool that can potentially identify trading opportunities; it’s a “must have” and is critical to most modern trading operations. The need to manage and monitor counterparty risk in addition to managing market risk, particularly with respect to portfolios containing complex instruments, require a focused and innovative approach to data analysis in order to safeguard trading operations.
Datawatch Desktop incorporates analytics for the four main risk pillars—counterparty, liquidity, credit, and investment (market)—while also incorporating additional functionality such as transaction-cost analysis (TCA), portfolio performance measurement and attribution, and pre-trade analytics. But having the tools available is just one part of the equation. Big-data analysis relies on the ability to draw information from various sources, not all of which are immediately open and transferrable. Datawatch Desktop is designed to directly ingest information from in-memory and relational databases, real-time data feeds, message buses, spreadsheets and complex event-processing engines, allowing it to reduce latency from the entire process. Crucially, it excels on the scale front, crunching data of any size, scaling up and down as users’ requirements change throughout the trading day.
In terms of visualization, one of the core functions of all big-data tools worth their salt, Datawatch Desktop also shines: It incorporates functionality supporting real-time portfolio risk views, investment performance across the board, and treemaps for the analysis of hierarchical data. Simplification, though, is similarly important, and it is here where Datawatch Desktop sets itself apart from other big-data tools on the market, providing users with the ability to view broad-level information before drilling down into it at will. In a saturated market with a handful of refined tools, Chelmsford, Mass.-based Datawatch stands out for its clinical approach to giving users what they actually need from big data, rather than the bells and whistles that serve little practical purpose. Given that this is the second year in a row it has won this category, it seems to be on the right track.
Technologies such as Datawatch Desktop have become an essential part of the buy-side toolkit. It’s not just a “nice to have”—a tool that can potentially identify trading opportunities; it’s a “must have” and is critical to most modern trading operations.
Adam Sussman joins Anthony Malakian to talk about Liquidnet's acquisition of OTAS, machine learning and AI, and what the buy side wants from analytics platforms.Subscribe to Weekly Wrap emails