Novel Solution for Real Time Challenges of ETL in Big Data
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Abstract
The big data which handles large amount of data in minute to minute situation is being supported by a new technology known as Extraction, Transformation and Loading. This technique has its own challenges while extracting the data, while processing it and transforming the data. After transforming data from one form to another, it should be loaded to the particular server into a particular form and into particular size. While performing these functionalities ETL faces challenging task, this task should be combated successfully for better QOS. In this proposed work various challenges to ETL is elaborated and solutions are derived to improve the performance of ETL. An artificial intelligence algorithm based support is recommended in this work for enhancing the better ETL performance over the challenges it faces.[1],[2]
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