Improving the Performance of the ETL Jobs |
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© 2023 by IJCTT Journal | ||
Volume-71 Issue-3 |
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Year of Publication : 2023 | ||
Authors : Dhamotharan Seenivasan | ||
DOI : 10.14445/22312803/IJCTT-V71I3P105 |
How to Cite?
Dhamotharan Seenivasan, "Improving the Performance of the ETL Jobs," International Journal of Computer Trends and Technology, vol. 71, no. 3, pp. 27-33, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I3P105
Abstract
ETL (extract, transform, load) jobs are responsible for extracting data from a variety of sources, transforming it into a consistent format, and loading it into a target data store. The performance of ETL jobs can significantly impact the overall performance of an organization's data management system. Several factors can affect the performance of ETL jobs, including the volume of data being processed, the complexity of the transformation logic, and the efficiency of the extraction and load processes. In this article, we will discuss some techniques for improving the performance of ETL jobs.
Keywords
Data warehouse, ETL testing, Extract Transform and Load (ETL), ETL performance, ETL optimization.
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