A Comprehensive Guide to ETL Process Research and Future Trends
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Timely and accurate decision-making provides a competitive advantage for each organization that needs to store and speedy access to the large volume of everyday transactional data. In the Data Warehouse (DW) environment, Extract, Transform, and Loading (ETL) plays a key technology that refines and integrates a large stream of heterogeneous operational and external data of any organization. The value of organizational data is significantly enhanced when content migration from various sources is done significantly by using the ETL process.In the last few years, the use of ETL for constructing an...
Timely and accurate decision-making provides a competitive advantage for each organization that needs to store and speedy access to the large volume of everyday transactional data. In the Data Warehouse (DW) environment, Extract, Transform, and Loading (ETL) plays a key technology that refines and integrates a large stream of heterogeneous operational and external data of any organization. The value of organizational data is significantly enhanced when content migration from various sources is done significantly by using the ETL process.In the last few years, the use of ETL for constructing and managing Data warehouses has been gaining popularity in various real-life applications as well as many industry applications require real-time integration and reporting over data acquired from heterogeneous data sources. ETL is a significant area of research for a well-established Data Warehouse environment.
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