Big Data

Automation of Data Warehouse, Extraction, Transformation and Loading Update Cycle

Download Now Date Added: Feb 2010
Format: PDF

Businesses today are largely dependent on access to right information at the right time. With vast amounts of data being processed on a minute to minute basis, it is of vital importance that managers and decision makers have access to the latest updates in their information database at all point of time. Even though most businesses invest large amount of money in implementing and maintaining data warehouse systems, there is often a time gap in the transfer of data updates from the various operational systems into the data warehouse systems. This is because in most systems that updating is done on a periodic basis. Moreover, if there are large amounts of data to be transferred (usually hundreds of terabytes), often problems of system overload crop up which halts the whole transfer process. The transfer of data from operating systems to the data warehouse is done through tools called the Extraction, Transformation, and Loading (ETL). The answer to all the problems mentioned earlier is automation of the ETL tools and application. An automation of Extraction, Transformation, and Loading (ETL) will provide many benefits like selection of best time for the transfer of data without any compromise on the usage of data warehouse. Moreover, an effective automation would also ensure that the data warehouse is simultaneously updated along with the operational systems thereby helping real time transaction processing work smoothly.