FICO has announced a community version of FICO Xpress Insight, a decision support application that enables data scientists to rapidly deploy any advanced analytic or optimisation model as a powerful business application.
Across industries, data scientists create powerful models to solve complex business problems. Yet, according to Gartner, more than half of data science projects are never fully deployed.
“The unrealised opportunity and resource expenditure is significant when models don’t reach the intended business use,” says Bill Waid, vice-president and GM of FICO Decision Management Suite. “The real business value of highly complex analytic models manifests when they’re placed in the hands of the business users and become an integral part of their operations.”
FICO Xpress Insight enables collaboration between the data scientist and the line of business user by taking complex analytic or optimisation models and turning them into simple point and click applications that help them make real business decisions. With FICO Xpress Insight, it’s easy to take any advanced analytic asset (such as an R or Python script) and turn it into a fully functioning application for business users.
FICO Xpress Insight delivers:
* A collaborative environment for data scientists and business users during model creation, while preserving their preferred modelling tools.
* A robust, yet flexible interface that is purpose built for rapidly deploying validated models in an application intended for the business user in business terms.
* Built-in user management, scenario management and file management, which reduces development effort by 70%.
* Business user enablement to run models, perform simulations, compare scenarios and visualise outcomes – all within a single framework.
Originally built to enable optimisation applications, FICO Xpress Insight now supports any advanced analytic model, including Python, SPSS and R. For data scientists trying to create decision support solutions, they can use Xpress Insight while also leveraging their existing investment in other analytic models and tools.