Create, Manage and Utilize Proprietary Data within Your Data Fabric
Are you reusing the valuable smart data generated during the investment process?
Analysts pre-process data by applying several transformations. They write rules to resolve gaps in data coverage, and define smart formulas for computing their factors. The by-product of their work is a rich dataset that often is not reused.
Our solution has handled terabytes of derived data. The following are key highlights of our solution:
- Reuse computations, scores, or items across all major analytical packages, including Matlab, SAS, R, Python, and Excel.
- Easily fork a derived data item for your own purposes while keeping track of the data lineage (provenance).
- Browse through a centralized library of available derived data and view statistics on each item.
- Re-compute your derived data when underlying data changes, which helps to make your factors more dynamic.