General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Cecilia Xie
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
    • E-mail: editor@ijcte.org
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IJCTE 2013 Vol.5(3): 484-487 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2013.V5.734

Revised Framework for ETL Workflow Management for Efficient Business Decision-Making

Saifur Rehman Malik, Azra Shamim, Zanib Bibi, Sajid Ullah Khan, and Shabir Ahmad Gorsi

Abstract—Business decision-making is not a simple task. There are many reasons for that but the main reason is data comes from heterogeneous operational sources of an organization. Therefore, it is difficult to organize and maintain especially if a huge volume of data is involved. A data warehouse is helpful in this regard as it can assists in business decision-making. Data collection and loading it into a data warehouse is difficult job because data sources are not in consistent form. This job usually consists of three main processes that involve extraction, transformation and loading. To extract the data from different sources, then transform it into a unified format and consequently load it into the warehouse, ETL (Extract, transform and load) tools are required. Nowadays, the majority of ETL tools organize workflow. An ETL workflow can be considered as a group of ETL jobs with dependencies between them. In this research paper a revised ETL workflow management framework which is based upon different considerations is proposed. These considerations along with the addition of the components in the workflow scheduling layer would help in making more effective and quality business decisions.

Index Terms—Data warehouse, ETL, ETL Tools, workflow management.

Azra Shamim is with the Faculty of Computer Science and Information Technology University Malaya (e-mail: azra.majeed864@yahoo.com).

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Cite:Saifur Rehman Malik, Azra Shamim, Zanib Bibi, Sajid Ullah Khan, and Shabir Ahmad Gorsi, "Revised Framework for ETL Workflow Management for Efficient Business Decision-Making," International Journal of Computer Theory and Engineering vol. 5, no. 3, pp. 484-487, 2013.


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