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Will enterprise information integration really displace traditional data warehousing, or just complement it?
If the term "enterprise information integration" isn't immediately clear, there's a reason: EII is a broad notion that raises more questions than it answers. How do you know if EII is right for your organization? What are the challenges of implementing EII? Above all, what does EII offer that isn't already covered by data warehousing and data extract, transform and load (ETL) software procedures? How is it different from customer data integration and other recent approaches to information integration?
All the acronyms are enough to make your head spin. In this article, we'll clarify EII and its role, particularly in business intelligence and data warehousing scenarios.
BREAK WlTH TRADITION
Rob Cardwell, CTO of EII software vendor MetaMatrix, says EII is about making distributed data "accessible and manageable, breaking through traditional barriers of location, structure, semantics and context." Surveying the offerings of MetaMatrix and competing vendors, it's clear that a federated query system is fundamental to making distributed data accessible, as it accesses multiple, heterogeneous data sources and brings back a single data set.
EII differs most from conventional ETL-oriented data warehousing in that it accesses, rather than moves, information. Keep in mind that ETL really isn't one standard procedure but multiple processes that vary according to what an organization needs. However, ETL generally involves data movement to a central repository or other files and subsystems, such as data marts, that support BI reporting. EII uses virtualization to present clients with a view of one consolidated information resource, hiding the federated query system that's actually drawing from multiple data resources. EII "plays the data where it lays," as some put it.
The number and complexity of data silos-disparate, disconnected resources beholden to a single department or .
user-continue to grow, outpacing IT's attempts to standardize ETL and data integration tools as well as efforts to update and maintain what still dominates most integration efforts: custom code. Regulatory compliance, real-time BI and new challenges involving convergence of structured, and unstructured information are putting even more pressure on conventional approaches.
EII could be a solution to some of these woes. Along with less movement, EII involves less extensive data transformation, focusing on combining...