• DocumentCode
    1791099
  • Title

    Validation of the data warehouse metrics using formal frameworks

  • Author

    Sharma, Ritu ; Kumar, Manoj

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Ambedkar Inst. of Adv. Commun., New Delhi, India
  • fYear
    2014
  • fDate
    12-13 July 2014
  • Firstpage
    239
  • Lastpage
    243
  • Abstract
    The DW consists of huge and complex set of data. Maintaining its quality is thus a matter of concern. The metrics are used to measure the quality factor of data warehouse. Several data model metrics of data warehouse have been proposed and validated in the literature to measure its quality attributes. There are two ways to validate the metrics. One is the formal validation and another is empirical validation. Our focus of study is on formal validation of metrics. Here in this paper, two formal frameworks have been surveyed for metrics validation namely; Briand´s framework and Zuse´s framework. Further, formal validation is illustrated with the help of Briand´s framework and Zuse´s framework by taking an example of each. Finally, both the formal frameworks have been compared and found easily understandable for validating the metrics formally.
  • Keywords
    data models; data warehouses; software maintenance; software metrics; software quality; Briand´s framework; Zuse´s framework; data model metrics; data warehouse metric validation; formal metrics validation; quality attribute measurement; quality factor measurement; Artificial intelligence; Complexity theory; Couplings; Length measurement; Size measurement; Briand´s framework; Data warehouse; Zuse´s framework; formal validation; metrics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Propagation and Computer Technology (ICSPCT), 2014 International Conference on
  • Conference_Location
    Ajmer
  • Print_ISBN
    978-1-4799-3139-2
  • Type

    conf

  • DOI
    10.1109/ICSPCT.2014.6884998
  • Filename
    6884998