Using data mining to unearth valuable insights means you can make better decisions with less time and effort than ever before.
But data that's acquired from various sources and scattered in multiple formats across the organization – or data that's not properly structured for different types of analysis – can present a challenge.
In this session, you'll learn how SAS Enterprise Miner can help you discover, explore and understand relationships in complex sets of data. Specific topics include:
- How to increase productivity and flexibility in developing analysis in SAS Enterprise Miner.
- How to use different configuration options for developing process flows.
- How to integrate different types of data sources, including market baskets, time-series data, textual data and others to develop enriched predictive models.
Laura Ryan is a Product Manager in Predictive Analytics Product Management at SAS. Her seven years at SAS have included additional roles as an instructor in the education division and a systems engineer in the inside sales division.
Ryan covers application data mining in SAS Enterprise Miner, including credit scoring, survival data mining, time-series data mining, incremental response modeling and insurance ratemaking. Her current initiatives include new products under development.