Data Integration is the process of integrating data from multiple sources and probably have a single view over all these sources and answering queries using the combined information. Once the data integrated, so that they form a unified new whole and give users the illusion of interacting with one single information system.
The reason for integration is twofold:
*First, given a set of existing information systems, an integrated view can be created to facilitate information access and reuse through a single information access point.
*Second, given a certain information need, data from different complementing information systems is to be combined to gain a more comprehensive basis to satisfy the need.
There is a manifold of applications that benefit from integrated information. For instance, in the area of business intelligence (BI), integrated information can be used for querying and reporting on business activities, for statistical analysis, online analytical processing (OLAP), and data mining in order to enable forecasting, decision making, enterprise-wide planning, and, in the end, to gain sustainable competitive advantages.
For customer relationship management (CRM), integrated information on individual customers, business environment trends, and current sales can be used to improve customer services.
Integration can be physical or virtual:
• Physical: Coping the data to warehouse
• Virtual: Keep the data only at the sources
The most complex and difficult part of integrating data is transforming data into a common format. Understanding the data to be combined and understanding (and possibly defining) the structure of the combined data requires both a technical and business understanding of the data and data structures in order to define how the data needs to be transformed.
Data integration
