Data integration suffers from an image problem. It has become synonymous with extract, transform and load. Likewise, ETL has been regarded as a data warehousing technology. Both of these viewpoints fail to reflect current capabilities, and they greatly inhibit enterprises…
Data integration suffers from an image problem. It has become synonymous with extract, transform and load. Likewise, ETL has been regarded as a data warehousing technology. Both of these viewpoints fail to reflect current capabilities, and they greatly inhibit enterprises in their attempt to integrate data to provide the information their business needs. Because of this short-sightedness, companies have lost opportunities to harness information as a corporate asset. It increases the cost of integrating data, encourages the creation of data silos and forces businesspeople to spend an inordinate amount of time filling the information gaps themselves through data shadow systems or reconciling data.
