IDEAS home Printed from https://ideas.repec.org/a/nwe/eajour/y2015i1p66-80.html
   My bibliography  Save this article

Methods for Heterogeneity Detection during Multi-Dimensional Data Mart Integration

Author

Listed:
  • Geno Stefanov

    (University of National and World Economy, Sofia, Bulgaria)

Abstract

The paper focuses on the detection of heterogeneities between multi-dimensional data marts. In many cases, data which resides in multiple and independently developed data marts is needed for decision-making. The multi-dimensional model introduces, in addition to the ER data model, dimension and fact entity. As a result of the multi-dimensional model elements, two groups of heterogeneities have been identified – dimension and fact. The former depends on differences between the dimensions’ hierarchies, their members, the names of the members, their levels and dimensions. The latter kind of heterogeneities occurs when facts in different data marts are in different names, values (inconsistent measures), formats or even on a different scale. Therefore, the paper examines and classifies the heterogeneities which can occur during the integration of independently developed data marts and four methods for heterogeneity detection are proposed and discussed. The methods are as follows: method for metadata extraction, method for detecting schema-instance heterogeneities, method for detecting heterogeneities among dimensions and method for detecting heterogeneities among facts. The paper ends with conclusions about the advantages of the proposed methods for heterogeneity detection during the integration of data marts.

Suggested Citation

  • Geno Stefanov, 2015. "Methods for Heterogeneity Detection during Multi-Dimensional Data Mart Integration," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 66-80, March.
  • Handle: RePEc:nwe:eajour:y:2015:i:1:p:66-80
    as

    Download full text from publisher

    File URL: http://www.unwe.bg/uploads/Alternatives/6_Stefanov.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    multi-dimensional model; data mart; method;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nwe:eajour:y:2015:i:1:p:66-80. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Vanya Lazarova (email available below). General contact details of provider: https://edirc.repec.org/data/unweebg.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.