Why Is Data Integration In Data Mining Important?
Data Integration is a data processing technique that collects data from different sources (such as data cubes, multiple databases, and flat files) and offers a unified view of the data to the users.
Data integration in data mining connects with issues such as duplicate data, inconsistent data, old systems, etc. Manual data integration can be achieved through middleware and applications.
There are primarily 2 major systems for data integration which are as follows:
Tight Coupling – In this method, the data warehouse is treated as an information recovery feature. The process is known as ETL which means Extraction, Transformation, and Loading.
Loose Coupling – In this method, an interface is offered that listens to a query from the user and transforms it to the source database and then sends the query directly to the reference databases and obtains a great result.
Frequently Asked Questions?
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