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Chapter 1 The Logical Data Warehouse

Put simply , the Logical Data Warehouse is a data system that encompasses the concepts of a traditional enterprise data warehouse , while including data from other data sources in addition to that from one ( or more ) core data warehouses .

Though the Logical Data Warehouse embodies something of a technological evolution , it does not serve as a replacement for current data warehouse practices . Instead , the Logical Data Warehouse permits IT organizations to make a large number of data sets and sources available for analysis via query tools and applications , all while improving decision-making and cost savings . There you have it , the “ what ” and the “ why ” of the Logical Data Warehouse .

Chapter 2

Common Patterns for Logical Data Warehouse

After numerous implementations of the Logical Data Warehouse , we have discovered six common patterns ( Figure 3 ), each with

different fundamental needs , and each delivering a new world of decision making , cost savings , and simplicity .

Chapter 3

Performance in a Logical Data Warehouse

It ’ s a common assumption that a virtualized solution would be slower than a persisted approach via ETL . However , Denodo has completed extensive testing using queries from the TPC-DS standard benchmarking test for decision support systems , revealing that typical reporting and analytical queries – usually involve aggregation operations over very large data sets – can be executed in a distributed , federated environment , such as the Logical Data Warehouse , with performance that matches that of querying the same data preloaded into a single data source . �

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