• DocumentCode
    2569265
  • Title

    Alliance Rules for Data Warehouse Cleansing

  • Author

    Arora, Rajiv ; Pahwa, Payal ; Bansal, Shubha

  • Author_Institution
    Dept. of IT, GPMCE, Delhi, India
  • fYear
    2009
  • fDate
    15-17 May 2009
  • Firstpage
    743
  • Lastpage
    747
  • Abstract
    Data cleansing is an activity performed on the data sets of data warehouse to enhance and maintain the quality and consistency of the data. This paper addresses the problems related with dirty data, entrance of dirty data and detection of dirty data in the data warehouse. The paper perceives the procedure of data cleansing from a different perspective. It provides an algorithm for the detection of errors and dirty data in the data sets of an already existing data warehouse. The paper characterizes the alliance rules based on the concept of mathematical association rules to determine the dirty and faulty data in data warehouse. The research marks the use of q-grams to determine the errors in a prominent way.
  • Keywords
    data analysis; data integrity; data mining; data warehouses; set theory; alliance rule; data cleansing; data consistency; data set error detection; data warehouse; dirty data detection; faulty data; mathematical association rule; Association rules; Data mining; Data warehouses; Decision making; Degradation; Enterprise resource planning; Performance analysis; Signal processing; Signal processing algorithms; Strategic planning; data cleansing; data marts; data warehouse;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    2009 International Conference on Signal Processing Systems
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3654-5
  • Type

    conf

  • DOI
    10.1109/ICSPS.2009.133
  • Filename
    5166887