Data integration refers to the process of accumulating data sets from disparate locations and combining those data sets together. Data integration incorporates the extract/transform/load (ETL) process, enterprise application integration (EAI), and the record linkage and consolidation process.

The ETL process comprises the sequence of applications that extract data sets from the various sources, bring them to a data staging area, apply a sequence of processes to prepare the data for migration into the data warehouse, and the actual loading process. Extraction focuses on selecting the right data to be extracted and determining how that data should be extracted. Frequently ETL tools provide system adapters that automatically generate code to perform the extraction, either on the source system or across the enterprise. After data is extracted, a number of transformations may be applied, in preparation for the data consolidation.

Enterprise application integration is encapsulated as intelligent middle-ware that provides the glue allowing multiple applications to interoperate. Enterprise application integration is not truly a product or a tool, but rather a framework of ideas comprising different levels of integration, including business process management, communications middleware, data standardization and transformation, and the application of business rules in process.

Consolidation is a catchall term for those processes that make use of collected metadata and knowledge to eliminate duplicate entities, merge data from multiple sources, and other data enhancement operations. That process is powered by the ability to identify some kind of relationship between any arbitrary pair of data instances, based on the...