Hot business - engines, usually providing a vast variety of high-end numerical schemes in a multi-strategy and multi-model environment as we find it in, say, process and risk control from chemical reactors, metallurgical plants to quantitative finance. Models usually are stochastic and partial differential equations solved by advanced finite element schemes to Montecarlo (better Quasi-Montecarlo) techniques. Usually the parameter identification (calibration) raises inverse-system problems that need special treatments, like regularization, ...
Blazing business - enabling the fast enough evaluation of such models (and this often means blazingly fast) one can forge the high-end numerics schemes and the next generation computing muscles as the NVIDIA Tesla 20 series of GPUs. The advances of such implementations can be measured in speed ups of thousands.
Cool business - to customize the analytics platform one wants to call the engines from a high-level declarative programming layer. For swifter time-to-insight you want to distribute tasks in a grid environment. Symbolic parallelization makes this easy. To increase transparency and reduce operational risk you need to apply the principle of consistent data and analytics management. In all this applications it is imperative to free info from silos, process analytics consistently and optimize systemwide transaction processing.
This requires link technologies and connectivities in your platform - With Mathematica we use the platform that empowers us to build large scale multi-model, multi-datasource and multi-timeframe systems.
Clever in any climate.