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Ultimate Software To Host Webcast On Predictive Analytics And Big Data For Human Capital Management

Ultimate Software (NASDAQ:ULTI)

WHAT: Ultimate Software , a leading cloud provider of people management solutions, will host a complimentary webcast that focuses on understanding how big data and HR come together to improve productivity, decrease costs, ensure compliance, proactively manage talent, and increase revenues.

The featured presenter for this webcast will be Laurie Bassi, chief executive officer at McBassi & Company, a leading company that uses behavioral economics to improve organizational performances. Bassi will discuss the evolution of big data as well as apply predictive analytics techniques that can solve a broad range of challenges related to human capital management. Participants will learn the fundamentals in getting started, best practices, pitfalls to avoid, and actionable insights that can make a strategic impact on their organizations.

WHEN: Thursday, June 13, 2013 at 2 p.m. Eastern Time

WHERE: Click here to register for Demystifying Predictive Analytics: Understanding How Big Data and HR Come Together

WHO: Laurie Bassi, CEO at McBassi & Company, is an internationally renowned HR analytics expert. She works with a range of clients—from start-up businesses to Fortune 100 businesses—to help each unleash human capability within their organizations. Her most recent books include the HR Analytics Handbook and Good Company: Business Success in the Worthiness Era, the winner of the 2012 Nautilus Gold Award for the best business/leadership book of the year.

Steve VanWieren, principal statistician and data scientist at Ultimate Software, is responsible for developing a range of analytic products, including the use of predictive analytics for effectively managing people. He is an expert on data integration, data privacy, and the use of data innovation in order to solve business problems. Previously, VanWieren worked as a vice president of Equifax, where he was responsible for measuring and improving the quality of U.S. consumer data as well as developing multiple statistical models related to risk, response, profitability, and fraud.

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