SHYFT ANALYTICS

Brand Owner Address Description
SHYFT ANALYTICS SHYFT Analytics, Inc. 350 Hudson Street New York NY 10014 SHYFT ANALYTICS; SHIFT ANALYTICS;ANALYTICS;Platform as a service (PAAS) featuring computer software platforms for integrating, managing, tracking, aggregating, filtering, and analyzing data for the life sciences industry to optimize clinical and commercial performance; Platform as a service (PAAS) featuring computer software platforms for data management, patient cohort creation, observational study design, patient cohort creation, and advanced analytics using Real World Evidence (RWE); Software as a service (SAAS) services featuring computer software for enabling the optimization, monitoring, and analyzing customer relationship and relevant third-party industry data for the life sciences industry; Software as a service (SAAS) services featuring software for managing, tracking, aggregating, filtering, and analyzing data for the life sciences industry; Software as a service (SAAS) services featuring software for managing, tracking, aggregating, filtering, and analyzing data for the purpose of Patient Care Coordination for the life science industry;
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. An analytics and data warehousing infrastructure and services system that uses an analytic rather than a transactional data model. The system preferably has at least one extracted source data store, at least one staging data store, and at least one analytic data store. The at least one staging data store preferably has at least one staging data table. The at least one analytic data store preferably has at least one analytic data table for storing transformed data. A staging data table loading algorithm may be used for populating the at least one staging data table with source data. A data transformation algorithm may be used for moving and transforming data from a staging data table into an analytic data store. Other algorithms that may be used in the present invention include algorithms for creating derived variables, creating event proxies, and restructuring data. In one preferred embodiment, the system is a data model based on a clinical rather than a financial understanding of healthcare.