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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2012 Vol.2(4): 419-422 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.157

Realistic Analysis of Data Warehousing and Data mining Application in Education Domain

Manjunath T. N., Ravindra S. Hegadi, Umesh I. M., and Ravikumar G. K.

Abstract—Data-driven decision support systems, such as data warehouses can serve the requirement of extraction of information from more than one subject area. Data warehouses standardize the data across the organization so as to have a single view of information. Data warehouses can provide the information required by the decision makers. Developing a data warehouse for educational institute is the less focused area since educational institutes are non-profit and service oriented organizations. In present day scenario where education has been privatized and cut throat competition is prevailing, institutes needs to be more organized and need to take better decisions. Institute’s enrollments are increasing as a result of increase in the number of branches and intake. Now a day, any reputed Institute’s enrollments count in to thousands. In view of these factors the challenges for the management are meeting the diverse needs of students and facing increased complexity in academic processes. The complexity of these challenges requires continual improvements in operational strategies based on accurate, timely and consistent information. The cost of building a data warehouse is expensive for any educational institution as it requires data warehouse tools for building data warehouse and extracting data using data mining tools from data warehouse. The present study provides an option to build data warehouse and extract useful information using data warehousing and data mining open source tools. In this paper we have explored the need of data warehouse / business intelligence for an educational institute, the operational data of an educational institution has been used for experimentation. The study may help decision makers of educational institutes across the globe for better decisions.

Index Terms—Data warehouse, data mining, analysis, ETL, BI.

Manjunath T. N. is a research scholar with Bharathiar University, Coimbatore, Tamil Nadu, India (e-mail: manjunath.tnarayanappa@rediffmail.com).
Ravindra S. Hegadi is with Dept of Computer Science, Solapur University, Solapur, Maharashtra, India (e-mail:ravindrahegadi@rediffmail.com). Umesh I. M. is with RV College of Engineering, Bangalore, Karnataka, India (e-mail: umesh.mphil@gmail.com).
Ravikumar G. K. is with Dr. MGR University, Chennai, Tamil Nadu, India(e-mail:ravi.gowda@gmail.com)


Cite: Manjunath T. N., Ravindra S. Hegadi, Umesh I. M., and Ravikumar G. K., "Realistic Analysis of Data Warehousing and Data mining Application in Education Domain," International Journal of Machine Learning and Computing vol. 2, no. 4, pp. 419-422 , 2012.

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