Nearly all predictive analytics – churn modeling, customer targeting, campaign optimization, fraud detection, and so on – require data from a variety of sources: applications, web logs, data warehouses, data marts, outside services, and more.
This “data problem” is a major challenge, with analytic teams often spending weeks or months collecting data, with relatively little time left for real analysis.
Or they instead limit themselves to what they can find in centralized marts or warehouses which may result in incomplete or inaccurate analytic results.
Join well known Analytics and Big Data expert Shawn Rogers of Enterprise Management Associates, Predictive Analytics expert Steven Hillion, and Data Virtualization expert David Besemer to learn the benefits of cross functional analytics and new streamlined approaches for accessing and analyzing multiple data sources.
