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DESCRIPTION:Click for Latest Location Information: http://edw2014.dataversity.net/sessionPop.cfm?confid=79&proposalid=6005\nFor decades now, data warehouses were extremely “brittle” in the face of new or changing business requirements.  Once loaded, their data repositories could not be repurposed without converting the existing data, a practice that can be ruinously expensive.  \nAs a result, data warehouse designers were forced to doom their projects to “death by architecture,” in which they insisted on perfect, up-front designs before data transform programming could begin.  Luckily, the new data modeling paradigms of hyper normalizing and hyper generalizing allow teams to readily adapt established warehouses in new directions without conversion script programming.   \nTeams can now start with a simple design that meets current business requirements, then steadily evolve the database as new business needs emerge.   These novel techniques have hundreds of successful implementations and strong support by vendors and practitioners.  \nIn this presentation, we will consider a couple of such case studies, then touch upon:\n\nWhy traditional data models become so expensive to update\nWhy “database refactoring” leaves much to be desired\nVariations upon standard normal forms that allow agile data engineering\nHow highly generalized data models enable model-driven development\nWhere tools can amplify the power of these new modeling techniques\n
DTSTART:20140427T143000
SUMMARY:W3: Agile Data Warehousing
DTEND:20140427T174459
LOCATION: See Description
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