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An Overview of ETL Techniques, Tools, Processes and Evaluations in Data Warehousing

Bilal Khan1, Saifullah Jan1,*, Wahab Khan1, Muhammad Imran Chughtai2

1 Department of Computer Science, City University of Science and Information Technology, Peshawar, Pakistan
2 Department of Computer Science and IT, Sarhad University of Science & Information Technology, Mardan, Pakistan

* Corresponding Author: Saifullah Jan. Email: email

Journal on Big Data 2024, 6, 1-20. https://doi.org/10.32604/jbd.2023.046223

Abstract

The extraction, transformation, and loading (ETL) process is a crucial and intricate area of study that lies deep within the broad field of data warehousing. This specific, yet crucial, aspect of data management fills the knowledge gap between unprocessed data and useful insights. Starting with basic information unique to this complex field, this study thoroughly examines the many issues that practitioners encounter. These issues include the complexities of ETL procedures, the rigorous pursuit of data quality, and the increasing amounts and variety of data sources present in the modern data environment. The study examines ETL methods, resources, and the crucial standards that guide their assessment in the midst of this investigation. These components form the foundation of data warehousing and act as a safety net to guarantee the dependability, accuracy, and usefulness of data assets. This publication takes on the function of a useful guide for academics, professionals, and students, despite the fact that it does not give empirical data. It gives students a thorough grasp of the ETL paradigm in the context of data warehousing and equips them with the necessary skills to negotiate the complex world of data management. This program equips people to lead effective data warehousing initiatives, promoting a culture of informed decision-making and data-driven excellence in a world where data-driven decision-making is becoming more and more important.

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Cite This Article

Khan, B., Jan, S., Khan, W., Chughtai, M. I. (2024). An Overview of ETL Techniques, Tools, Processes and Evaluations in Data Warehousing. Journal on Big Data, 6(1), 1–20. https://doi.org/10.32604/jbd.2023.046223



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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