My partner, Evan Levy, teaches a great class at TDWI called Architectural Options for Data Integration. The class talks about the various options for data integration, including extraction, transformation, and loading (ETL) for moving data from point A to point B; master data management (MDM), enterprise application integration (EAI) for enabling business applications to exchange information; enterprise information integration (EII) to support federated queries; and MDM for operationally reconciling the data across different systems. He also talks about the data warehouse for cross-functional analytical data, too, but most of the attendees already have that down. Some of these solutions acknowledge the meaning of the data and some don't. Some of these embed data quality and business rules and some don't. Some of them are just mechanisms for data migration, not integration. If you're interested, Evan will be teaching this class at TDWI's World Conference in San Diego this August.
The point here is to understand the problem you're trying to solve, and then identify which class of data integration solutions is the best approach for you, and start gathering functional requirements. Then you'll be ready to identify a short-list of vendors.
And, speaking of vendors, they're not making it easy for us are they? There are enterprise service bus vendors claiming to be MDM, data warehouse vendors claiming to do EII, and MDM vendors purporting to be your analytical database. It's enough to make me want to uncork a bottle and listen to some Mojo Nixon.
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