Data Mining and Data Warehouses
Michael Di Stefano · 2005
Analysis of large data sets comes at a cost. The cost benefit ratio is the level of complexity of the analysis versus the compute infrastructure (e.g. hardware, software, network, etc.) required to support the analysis. As the complexity of the analysis increases, more extensive infrastructure is required. This use case study highlights that the business is not realizing the full potential of the data in the Data Warehouse. This is due to many reasons including the physical limitations imposed on the warehouse's ability to perform queries/analysis. The Data Grid architecture offers an alternative to traditional Data Mining and Warehousing infrastructures. Not all Data Grid implementations lend themselves to this use case, only those that meet specific criterion; the details of which are discussed. Presented are different methods in which a Data Grid can be used in a Data Warehousing application. A new of data warehousing is architecture is introduced, the Real-Time Data Warehouse. As with all of the example use cases discussed in this book, the Application Definition Expressions are discussed and the Quality of Service (QoS) vs. Application Requirement Quadrant Graph is generated.