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
Link To Document :
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