Implementing and Maintaining Analytics Models

Everybody talks about predictive models and reads about insightful results from building advanced analytics models on small and big data. But once you build a model, how do you ensure continuing usability of the model? How will your model adapt to a changing environment? This presentation will illustrate a typical data model life cycle and will touch on the operational, technical, and analytics subject matter expertise required to successfully utilize analytics models. Examples and case studies of multiple model implementations will build best practices and lessons learned. You Will Learn * Utilizing analytics models successfully requires a life cycle approach * Subject matter expertise (operational, technical, analytical) is a critical component of analytics * Best practices (and how we learned them the hard way) Geared To * Analytics, big data, and business intelligence sponsors and stakeholders * Data architects, integrators, and modelers