Motivation for Data Integration Systems

• Historical view: integration-by-hand
• Users can focus on specifying what they want, not on how to obtain what they want. Instead of finding relevant sources, interacting with every source and combining data from different sources, a user can ask queries in a unified way.
  Particular examples:
  • Desire for reports that describe all parts of a merged organization (bank mergers, car dealerships, etc.).
• Facilitates decision support applications (OLAP, Data mining)

  OLAP

  (On-Line Analytical Processing) is making financial, marketing or business analysis to be able to make business decisions on a collection of detailed data from one or more data sources. The analysis is done through asking large number of aggregate queries on the detailed data.

  Data Mining

  is discovering knowledge from a large volume of data. Statistical rules or patterns are automatically found from the raw collection of data.