• DocumentCode
    2873857
  • Title

    On data integration and data mining for developing business intelligence

  • Author

    Ping-Tsai Chung ; Chung, Samuel H.

  • Author_Institution
    Dept. of Comput. Sci., Long Island Univ., Brooklyn, NY, USA
  • fYear
    2013
  • fDate
    3-3 May 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Business Intelligence (BI) allows a corporation´s executives to acquire a better understanding of their customers, the market, supply and resources, and competitors in order to make effective strategic decisions. BI technologies provide historical, current and predictive views of business operations such as reporting, online analytical processing, business performance management, competitive intelligence, benchmarking, and predictive analytics. Web Services technologies responded quickly to help such evolution and in many situations the Web Services application is driving businesses and dictating a new way of doing business. Web information usually contains multimedia data with unstructured fashions. Through the effective analysis of company´s Web information, we could make effective market analysis, compare customer feedback on similar products, discover the strengths and weaknesses of their competitors, retain highly valuable customers, and make smart business decisions. In this paper, we discuss two case studies on data integration and data mining. The first case is for the traditional data analytics using relational database techniques such as Oracle database and Cognos BI tool for integrating and mining a company´s web site. The second case is for multimedia data analytics using Monago database and Pentaho BI tool for integrating and mining multimedia data presented in a company´s web site. We compare both cases in aspects of Data Integration, Metadata, Query Performance and Data Analytics. Finally, we present experimental results for using the above data mining techniques and tools to better understand features of each customer group and develop customized customer reward programs.
  • Keywords
    Web services; Web sites; competitive intelligence; data analysis; data integration; data mining; meta data; multimedia systems; query processing; relational databases; BI technologies; Cognos BI tool; Monago database; Oracle database; Pentaho BI tool; Web services technologies; business intelligence; company Web site mining; customer group features; customized customer reward programs; data integration; metadata; multimedia data analytics; multimedia data mining; query performance; relational database techniques; Bismuth; Business; Data integration; Data mining; Relational databases; Web sites; Data integration; business intelligence; data mining; database; web server;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Applications and Technology Conference (LISAT), 2013 IEEE Long Island
  • Conference_Location
    Farmingdale, NY
  • Print_ISBN
    978-1-4673-6244-3
  • Type

    conf

  • DOI
    10.1109/LISAT.2013.6578235
  • Filename
    6578235