A Data Mart Approach For A Centralized Egovernance Data Warehouse
With many computer applications in place, large quantities of data have been collected over a period of years. Private organizations recognized that there is value in the historical data of their own organizations and have undertaken projects to build Data Warehouses (DW) to make the data accessible in a meaningful and timely manner through data mining and querying tools. But mostly in Government organizations, it is not so. DW and data mining technologies have extensive potential applications in the government – in various Central Government sectors such as Agriculture, Rural Development, Health and Energy etc.. We had selected this problem to design a feasible architecture in the context of Central Government of India. The basic aim of this paper is we had studied DW architectures implemented in private organisations and gave a thought to design a data mart approach architecture for a centralized eGovernance DW which covers all the major departments in the Central Government of India emphasizing the ways and means to select the subject-oriented areas for populating the data marts, implementation parameters, quality factors and at the end touched the issues like access and security involved in them. Also, we had covered presented a small case-study of a simple DW implemented in Andhra Pradesh State Government, India.
Abdullah,The Case for an agri data warehouse: enabling analytical exploration of integrated agricultural data. In: Proceedings of the IASTED International Conference on Databases and Applications (DBA 2004).
Agosta, Data warehouse size depends on the size of the business problem. DM Rev. v13 i16. 16-17, 2003.
Bieber M., Data Warehousing in Government, DM Rev, 2008.
Chaudhuri and Dayal, Surajit Chaudhuri , Umeshwar Dayal, An overview of data warehousing and OLAP technology, ACM SIGMOD Record, v.26 n.1, p.65-74, March 1997.
Lei-da Chen , Khalid S. Soliman , En Mao , Mark N. Frolick, Measuring user satisfaction with data warehouses: an exploratory study, Information and Management, v.37 n.3, p.103-110, April 2000.
Hackney, D.,Architectures and Approaches for Successful Data Warehouses, Oracle White Paper, 2002.
Harper, Data warehousing and the organization of governmental databases. IGI Publishing, 2004.
India, N.I.C., 2004. Districts of India: A Gateway to Districts of India on the web, http://www.districts.nic.in, 2004.
Inmon, William H. Inmon, Building the Data Warehouse, John Wiley & Sons, Inc., New York, NY, 2002.
Kimball, Ralph , Margy Ross, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, John Wiley & Sons, Inc., New York, NY, 2002.
Oliveira, Taxonomy of data quality problems. In: Proceedings of the International Workshop on Data and Information Quality, 2005.
Shankaranarayanan, The role of process metadata and data quality perceptions in decision making: an empirical framework and investigation. J. Info. Technol. Manage. v17 i1. 50-67, 2006.
V.V. Subrahmanyam, M.N. Doja, Development Trends in the Field of Data Warehousing and OLAP, in the proceedings of Emerging Trends in Computer Science (ETCS-2007), MIET, Meerut, Pg Nos: 218-226, 2007.
V.V. Subrahmanyam, M.N. Doja, A Survey of Conceptual Models for Data Warehouse Design, in the prodeedings of International Conference on Data Management (ICDM 2008), Institute of Management Technology, Ghaziabad, UP. Pg Nos: 239 – 246, Mac Millan Advanced Research series, 2008.
V.V. Subrahmanyam, M. N. Doja, An UML Based Approach for Designing the Conceptual Model of a Data Warehouse, in the proceedings of 3rd National Conference on Methods and Models in Computing (NCM2C-2008), Jawaharlal Nehru University (JNU), INDIA, Pg Nos: 3-11, published by Allied Publishers, 2009a.
V.V. Subrahmanyam, M.N. Doja, Design Considerations for Building a Data Warehouse for an Open University System, in the proceedings of International Conference in Computing Technologies (ICONCT-09) Mepco Schlenk Engineering College, Sivakasi, Tamilnadu , INDIA, Pg.Nos: 401-406, 2009b.
Watson, Data warehousing failures: case studies and findings, Data Warehousing. v4 i1. 44-55, 1999.
Widom, Jennifer Wisdom, Research problems in data warehousing, Proceedings of the fourth international conference on Information and knowledge management, p.25-30, November 29-December 02, 1995, Baltimore, Maryland, United States, 1995.
William E. Winkler, Methods for evaluating and creating data quality, Information Systems, v.29 n.7, p.531-550, October 2004.
Reference website http://www.home.nic.in, 2010.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (Creative Commons Attribution License 3.0 - CC BY 3.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).