Get more machine learning projects into production by leveraging a shared library of derived data attributes across your enterprise.
Build and manage a shareable library of data attributes calculated from both processed and raw data.
These business assets can be exposed and leveraged across the enterprise to help you get more value from your machine learning-enabled business services.
Create and manage a shared set of specific feature definitions to standardize the interpretation of extracted business value from sources of raw and processed data.
- Discover more relevant signals and context-aware insights by defining and leveraging calculations such as “days since last purchase” or “number of transactions over a period of time.”
- Build definitions once, then share and reuse across all capabilities, use cases, teams, and organizational silos.
Feature engineering and management has traditionally been a time-intensive step of any analytic process, requiring the expertise of data science teams.
As a result, business users have been unable to explore the possibilities and potential of data directly. FICO’s approach to feature management democratizes the use of these predictive variables across functional teams and business silos. Leverage and reuse a consistent and reliable set of features to drive more intelligent real-time decisioning across use cases and save considerable time and effort getting your predictive models and other machine learning projects into production.