• E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

INTERNATIONAL JOURNAL OF INVENTIONS IN ENGINEERING & SCIENCE TECHNOLOGY

International Peer Reviewed (Refereed), Open Access Research Journal
(By Aryavart International University, India)

Paper Details

DEVELOPING A MATHEMATICAL MODEL FOR THE ENHANCED EFFICACY OF THE INFORMATION DISTRIBUTION CENTRE/DATA WAREHOUSE

Ram Khanna

120 - 126 Vol. 5, Jan-Dec, 2019
Receiving Date: 2019-10-20;    Acceptance Date: 2019-11-16;    Publication Date: 2019-11-20
Download PDF

Abstract

Developing an information distribution centre is another discipline and has no substantial system for its advancement cycle. At present, there are three advancement approaches for building an information distribution centre: Data-driven. Objective driven and User-driven. These advancement approaches are looked at depending on specific boundaries, and by this correlation, another Hybrid multidimensional improvement system has been developed. This Hybrid multidimensional Data model joins Data-driven strategies with Business-driven, which is a Goal-driven procedure. We have expressed in this paper that this model beginnings by gathering Business prerequisites and determining Fact and Dimension tables alongside its different imperatives, which characterize their relations. After which we can construct a consistent design of the model. Which, thus, could be formed into an actual model and can be populated by information for Mining and Analysing. Can think about this new multidimensional model on similar boundaries used to analyses the expressed three procedures, and accordingly, we can concoct upgraded highlights

    References

  1. Franconi E., Introduction to Data Warehousing, Lecture Notes, http://www.inf.unibz.it/~franconi/teaching/2002/cs636/2 ,2002
  2. W. H. Inmon, “Building the Data Warehouse, 3th Edition”, John Wiley, 2002
  3. Watson, H., Haley, B.: Managerial Considerations. In Communications of the ACM, Vol. 41, No. 9 (1998)
  4. List, Beate, et al. 'A comparison of data warehouse development methodologies case study of the process warehouse.' International Conference on Database and Expert Systems Applications. Springer, Berlin, Heidelberg, 2002.
  5. Widom, J. Research Problems in Data Warehousing, in Proc. 4th Int. Conf. „on Information and Knowledge Management, 1995
  6. Kimball, R. The data warehouse toolkit. John Wiley & Sons, 1996
  7. McGuff, F. Data modelling for data warehouses. http://members.aol.com/fmcgufYdwmodel/dwmodel.htm, 1996
  8. Inmon, W. H.: Building the Data Warehouse. Wiley & Sons (1996)
  9. Golfarelli, M., Maio, D., Rizzi, S.: Conceptual Design of Data Warehouses from E/R Schemes. In: Proceedings of the 31st HICSS, IEEE Press (1998)
  10. Boehnlein, M., Ulbrich vom Ende, A.: Business Process Oriented Development of Data Warehouse Structures. In: Proceedings of Data Warehousing 2000, Physica Verlag (2000)
  11. Westerman, P.: Data Warehousing using the Wal-Mart Model, Morgan Kaufmann (2001)
  12. Poe, V.: Building a Data Warehouse for Decision Support. Prentice Hall (1996)
Back