• DocumentCode
    2459161
  • Title

    A Meta-language for MDX Queries in eLog Business Solution

  • Author

    Bergamaschi, Sonia ; Interlandi, Matteo ; Longo, Mario ; Po, Laura ; Vincini, Maurizio

  • Author_Institution
    Dept. of Inf. Eng., Univ. of Modena & Reggio Emilia, Modena, Italy
  • fYear
    2012
  • fDate
    1-5 April 2012
  • Firstpage
    1417
  • Lastpage
    1428
  • Abstract
    The adoption of business intelligence technology in industries is growing rapidly. Business managers are not satisfied with ad hoc and static reports and they ask for more flexible and easy to use data analysis tools. Recently, application interfaces that expand the range of operations available to the user, hiding the underlying complexity, have been developed. The paper presents eLog, a business intelligence solution designed and developed in collaboration between the database group of the University of Modena and Reggio Emilia and eBilling, an Italian SME supplier of solutions for the design, production and automation of documentary processes for top Italian companies. eLog enables business managers to define OLAP reports by means of a web interface and to customize analysis indicators adopting a simple meta-language. The framework translates the user´s reports into MDX queries and is able to automatically select the data cube suitable for each query. Over 140 medium and large companies have exploited the technological services of eBilling S.p.A. to manage their documents flows. In particular, eLog services have been used by the major media and telecommunications Italian companies and their foreign annex, such as Sky, Media set, H3G, Tim Brazil etc. The largest customer can provide up to 30 millions mail pieces within 6 months (about 200 GB of data in the relational DBMS). In a period of 18 months, eLog could reach 150 millions mail pieces (1 TB of data) to handle.
  • Keywords
    business data processing; competitive intelligence; data analysis; data mining; query languages; relational databases; MDX queries; OLAP; Web interface; business intelligence; data analysis tool; data cube; eLog business solution; meta-language; relational DBMS; Companies; Data analysis; Data models; Data warehouses; Production; Servers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering (ICDE), 2012 IEEE 28th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1063-6382
  • Print_ISBN
    978-1-4673-0042-1
  • Type

    conf

  • DOI
    10.1109/ICDE.2012.100
  • Filename
    6228210