TDWI World Conference Fall November 7-12, 2010

CBIP

Prerequisite: None

Tony Rathburn

Traditionally, organizations use data tactically—to manage operations. For competitive edge, leading organizations use data strategically—to expand the business, improve profitability, reduce costs, and market more effectively. The mining of data for predictive indicators creates information assets that an organization can leverage to achieve these strategic objectives. Predictive analytics is a new component in an enterprise's decision support system (DSS) architecture. It complements and interlocks with other "retrospective" DSS capabilities.

You Will Learn

• Basic principles and terminology for predictive analytics
• Who is utilizing predictive analytics, and why
• Common project pitfalls and how to avoid them
• Project performance and maintenance issues
• How to define business objectives for a decision support system
• How to get started

Geared To

• IT/IS executives and managers: CIOs, CKOs, CTOs, functional officers, technical directors, and project managers; line-of-business executives and functional managers: risk managers, customer relationship managers, business forecasters, inventory flow analysts, financial forecasters, direct marketing analysts, medical diagnostic analysts, e-commerce company executives; technology planners who survey emerging technologies to prioritize corporate investment; consultants whose competitive environment is intensifying and whose success requires competency with data mining and related emerging information technologies