Cambridge, MA (PRWEB) March 03, 2014
Talent Analytics, Corp. today announced Advisor 4.0™, a major release of their predictive analytics platform. Available in early April, this update makes it possible to deploy predictive talent models, created in any predictive analytics system, directly inside Advisor. Examples include R, Rapid Miner, SAP, SAS®, Weka, IBM SPSS and other PMML compliant analytics tools.
Chief Scientist Pasha Roberts stated, “this release enables analysts to use their tool of choice for modeling, while providing a state-of-the art, online system to deploy the models into ongoing talent operations. Advisor 4.0 transforms the predictive analytics deployment phase from being a final hurdle into a simple, tested step.”
Dr. John Elder, Founder & CEO of Elder Research commented, “predictive analysis and data gathering are a positive feedback loop, a loop that continuously learns. Advisor 4.0 enables hiring managers and line of business managers to easily deploy multiple predictive models into employee operations, and continuously improve models as new data and analyses are completed.”
“In high volume employee areas, even marginal performance or attrition improvements result in significant bottom line results,” said CEO Greta Roberts. “When predictive models show that one bad hire wipes out the value of 3 great hires, hiring decisions modify instantly to add analytics to the hiring process. Advisor 4.0 makes the deployment of predictive models not only possible, but easy.”
To learn more about Advisor 4.0, which will be available in April 2014, please visit: http://www.talentanalytics.com/technology/advisor/
For more about the ROI of using predictive models in the hiring process, read this scenario: http://bit.ly/1jyd34Y
About Talent Analytics, Corp.
Talent Analytics, Corp., is a privately held corporation headquartered in Cambridge, Massachusetts. Its predictive talent analytics platform Advisor™, uses a quantitative approach for predicting top and bottom performers, predicting employee churn and predicting top performing data scientists. For more information visit http://www.talentanalytics.com, contact Talent Analytics at 617.864.7474 or email info(at)talentanalytics(dot)com.