The people who create sophisticated analytical models and those who manage corporate data warehouses rarely interact when they have every reason to. For years, analytical modelers have done their own data collection, integration, and scoring as part of the process involved in creating predictive models, however data management tasks have become a bottleneck impacting time to market. Often, they have no alternative since the organization’s data warehouse—if one exists—usually doesn’t contain the right data at the right level of detail in the right format. And data administrators don’t usually permit analysts to create tables or add new data elements on an ad hoc basis or submit long-running, complex queries. But today, as analytical workstations and databases become more tightly integrated, there is no excuse why these two groups shouldn’t work more closely together to improve the performance and productivity of analytical models. This Webinar will explore the dimensions of the cultural divide and make recommendations for how to overcome it.
You will learn:
Individual, Student, & Team memberships available.