According to TDWI surveys, self-service practices constitute one of the fastest-growing segments within data management and analytics today. These practices include self-service data exploration, data prep, data visualization, and other analytics. Although self-service practices were developed to help mildly technical business users, technical data professionals also find them to be a productivity boost. With these two very important user groups demanding self-service, it behooves us to supply the demand and get it right.
However, successful self-service involves many requirements, ranging from data integration and modeling through business-friendly metadata to end-user tools and governance. This talk will discuss the many data requirements for self-service data practices to help improve the success of organizations implementing them.