We use cookies to personalize content and ads and to analyze our traffic.

We also share information about your use of our site with our advertising and analytics partners. See details.

Open:FactSet now features a user community forum!

Find us under the Community menu!

Quantitative Techniques in Python (QTPy)

Solution by Kuberre Systems, Inc.

Added to Marketplace for Purchase: Mar. 06, 2019

Highlights
  • Benefit from ready-to-be-consumed python objects that are pre-populated from federated data sources in a distributed computing environment. Pre-built associations in python objects eliminate complex joins and data access bottlenecks from databases at run time.
  • Leverage a federated architecture to quickly integrate and explore new data sets with absolute ease and seamless scalability.
  • Offload Data Engineering from Data Science and accelerate your quantitative projects in Python/R.
Solution Details
Built on Kuberre EDM and Python as the core development environments, Kuberre’s Quantitative Techniques in Python (QTPy) is a comprehensive PaaS technology solution designed for Data Science and Quantitative projects. QTPy offloads the enterprise data management burden to Kuberre while seamlessly providing massively scalable access to underlying data through fully associated Python objects. Clients using this service can start building compelling data science projects in just a couple of weeks.
Firm Information
Kuberre Systems, Inc. is a Data Management & Analytics company that provides EDM software and EDM derived, fully managed solutions to some of the most reputable asset managers in the world. Kuberre EDM is built on a set of pre-cast components that enable clients to find their perfect balance between a buy and build solution. For clients who would like to outsource data management responsibilities, Kuberre offers EDM derived solutions such as QTPy, Security Master and an Investment Data Platform.