In today's ever-changing economic environment, there is ample opportunity to leverage the numerous
sources of time series data now readily available to the savvy business decision maker. This time series data can be
used for business gain if the data is converted to information and then into knowledge. Data mining processes,
methods and technology oriented to transactional-type data (data not having a time series framework) have grown
immensely in the last quarter century. There is significant value in the interdisciplinary notion of data mining for
forecasting when used to solve time series problems. The intention of this talk is to describe how to get the most
value out of the myriad of available time series data by utilizing data mining techniques specifically oriented to data
collected over time; methodologies and examples will be presented.