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EII Crosses Data Boundaries

Why not use data warehouses instead? Although similar to EII products in practice, data warehouses play a vastly different role. Whereas EII works with data in real time, data warehouses are designed for historical and analytical applications. Data warehouses require data replication, which in turn requires a host of applications and processes to support the replication, cleansing and categorization of data as it is pulled from corporate sources and pushed into a warehouse. EII products, in contrast, open a window on raw data while leaving it in its place.

But don't scrap your warehouse yet: Although some EII platforms can replicate data, that is not their primary purpose. And though EII products can do many of the tasks required to create and maintain a data warehouse, they cannot replace a large-scale warehouse because of EII's focus on real-time integration and lack of comprehensive ETL (extract/transform/load) functionality.

Another term commonly heard in the same breath as EII is virtual database. The implication is that database tables--such as orders, customers and inventory--from multiple sources will be magically accessible over a virtual database, represented by an EII platform. Rather, virtual databases are containers, like physical databases, that group data constructs, such as tables and views, and provide an interface for application and developer access. Nice, to be sure, but not the be-all and end-all of EII.

Give the People What They Want

A number of benefits are driving EII adoption. Some are business-related, while others are focused solely on IT.

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