ETD

Digital archive of theses discussed at the University of Pisa

 

Thesis etd-11152017-200048


Thesis type
Tesi di laurea magistrale
Author
KAOUEL, AMEL
URN
etd-11152017-200048
Thesis title
Adozione di strumenti per l'analisi e il controllo delle attivita legate alle spedizioni internazionali
Department
INFORMATICA
Course of study
INFORMATICA PER L'ECONOMIA E PER L'AZIENDA (BUSINESS INFORMATICS)
Supervisors
relatore Prof. Turini, Franco
Keywords
  • data mart
  • power bi
  • tabular data model
Graduation session start date
01/12/2017
Availability
Full
Summary
Abstract

Nowadays, to ensure the increasing need of data analysis, enterprises propose to monitor the business by means of Business Intelligence platforms that produce high added value information. The challenge is not only about building a data warehouse but also about to be expert in presenting business intelligence solutions in self-service mode. Today we are facing an increasing number of non-specialized population that needs to access advanced analytics and reports without the intervention of technical teams. Thus, when Business intelligence is available in self-service mode, the advantage is double: managers can make decisions faster and technical teams reduce the time usually allocated to respond to customer’s queries and instead, use it to improve data management strategies. In this project, we describe the process of designing and implementing a data warehouse that covers all the aspects of air freight, sea freight and ground transportation. The business consists of four main processes order, shipment, distribution and billing. During the project, the works has been organized in three parts: The first is related to data warehouse development, the second concerns the SSAS tabular data modeling and last one refers to reporting. Thus, this report follows up from data warehouse design and continues with data marts modeling, then extract transform load procedures to populate the data warehouse and its corresponding data marts, finally the reporting system. This system is based on self-service BI technology in which the specialist builds reports that are shared in the cloud and used by managers on mobile apps or desktop.
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