Pervasive Business Intelligence

Turricchia, Elisa (2013) Pervasive Business Intelligence, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria elettronica, informatica e delle telecomunicazioni, 25 Ciclo. DOI 10.6092/unibo/amsdottorato/5232.
Documenti full-text disponibili:
[img]
Anteprima
Documento PDF (English) - Richiede un lettore di PDF come Xpdf o Adobe Acrobat Reader
Download (2MB) | Anteprima

Abstract

In the last few years, a new generation of Business Intelligence (BI) tools called BI 2.0 has emerged to meet the new and ambitious requirements of business users. BI 2.0 not only introduces brand new topics, but in some cases it re-examines past challenges according to new perspectives depending on the market changes and needs. In this context, the term pervasive BI has gained increasing interest as an innovative and forward-looking perspective. This thesis investigates three different aspects of pervasive BI: personalization, timeliness, and integration. Personalization refers to the capacity of BI tools to customize the query result according to the user who takes advantage of it, facilitating the fruition of BI information by different type of users (e.g., front-line employees, suppliers, customers, or business partners). In this direction, the thesis proposes a model for On-Line Analytical Process (OLAP) query personalization to reduce the query result to the most relevant information for the specific user. Timeliness refers to the timely provision of business information for decision-making. In this direction, this thesis defines a new Data Warehuose (DW) methodology, Four-Wheel-Drive (4WD), that combines traditional development approaches with agile methods; the aim is to accelerate the project development and reduce the software costs, so as to decrease the number of DW project failures and favour the BI tool penetration even in small and medium companies. Integration refers to the ability of BI tools to allow users to access information anywhere it can be found, by using the device they prefer. To this end, this thesis proposes Business Intelligence Network (BIN), a peer-to-peer data warehousing architecture, where a user can formulate an OLAP query on its own system and retrieve relevant information from both its local system and the DWs of the net, preserving its autonomy and independency.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Turricchia, Elisa
Supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Ciclo
25
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Business Intelligence 2.0, Distributed Data Warehouses, Query Reformulation, Lean Development, OLAP Query Personalization and Recommendation, Agile Release Scheduling, Similarity Measures in Multidimensional Contexts,
URN:NBN
DOI
10.6092/unibo/amsdottorato/5232
Data di discussione
19 Aprile 2013
URI

Altri metadati

Statistica sui download

Gestione del documento: Visualizza la tesi

^