Data integration is generally implemented in data warehouses (DW) through specialized software that hosts large data repositories from internal and external resources. Data is extracted, amalgamated and presented as a unified form. It primarily supports the analytical processing of large data sets by aligning, combining and presenting each data set from organizational departments and external remote sources to fulfill integrator objectives.

On the surface, data integration sounds like a simple idea. Because many organizations store information on multiple databases, they need a way to retrieve data from different sources and assemble it in a unified way. For example, let's imagine that an electronics company is preparing to roll out a new mobile device. The marketing department might want to retrieve customer information from a sales department database and compare it to information from the product department to create a targeted sales list.

Data integration is the combination of technical and business processes used to combine data from disparate sources into meaningful and valuable information. A complete data integration solution delivers trusted data from various sources. Data integration is a process in which heterogeneous data is retrieved and combined as an incorporated form and structure.