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Tesi etd-02072016-124628

Thesis type
Tesi di laurea magistrale
Business Intelligence Tool: a new way of analysis
Corso di studi
relatore Prof. Capodaglio, Alessandro
Parole chiave
  • Business Intelligence
Data inizio appello
Riassunto analitico
From the second half of the twentieth century to the present, the technological evolution has strongly influenced the development of modern society in many aspects, from the change in the way of doing business to those socio-economic aspects, improving the ease of access to services offered and the ability to automate various operations through all economic sectors.<br>Technological progress has brought into the market, and therefore to all individuals who have access to the market, a number of devices that have enabled us to meet most of the needs of both consumers and entrepreneurs. Examples of devices that have deeply influenced the technological evolution can be: computers, mobile phones, World Wide Web, the birth of computing devices, data collection and many others. All of them have in common the fundamental characteristic of collecting information in the form of data, which is the base of the “modern era”.<br>The data collection process has always existed: i.e. Egyptians used to make the population census, abacus was introduced by the Sumerian to track the accounts of one or more trades and so on. Throughout the centuries, populations have introduced new ways of collecting data; the big difference between the ancient times and today is mainly due to the available technology. The modern technology allows us to gather and collect large amount of information and transform it into data; this data is used by companies to understand better market scenarios in which they operate, to figure out the needs of the consumers and meet their demand in order to achieve a competitive advantage in the market. To fulfill this request, managers and companies, must use high processing capacity tools which involve a long term view, big investments both in technologies and management changing and high employees’ skills. Today, when it comes to these activities and scenario, the recurring theme is “big data”.<br>To get to big data one must first understands what has been the evolution of the process analysis, designed to transform data into information that can be used by company management to support the decision-making process. This evolution is mainly identified by two systems: Business Intelligence and Business Analytics. These two systems have been fundamentals for the evolution of technology, management and business of the last twenty years. They have led companies to review the way they operate, basing decisions on data; data that might be collected in numerous quantity. The changing was possible by having the possibility to use the most advanced information technologies, that allowed companies to increase significantly the amount of data collected. The main difference between the Business Intelligence and Business Analytics systems and big data lies in the fact that the first ones analyze consolidated figures of the past, to get information and make predictions of the future. the second one, instead, bases its analysis on past data to project them into a future with greater accuracy, identifying trends and advising consumers on which products they might be interested in.<br>The difference is embodied in the questions to which these systems try to answer:<br>- The BI / BA systems answer to &#34;why&#34; something happens and only afterwards to “what” they should do in order to achieve the goal;<br>- The big data systems answer to the question &#34;what&#34; will happen and only afterwards to &#34;why&#34; something had happened, but only if required.<br>The change is mainly based on the approach used to observe and analyze data.<br>The importance of these tools is already established in the market.<br>The goal of this study is to collect, define and analyze the developments undertaken over a three year period of the most used tools by the companies, and to highlight that now all the actors of the market should seek to data analysis as a first resource for managerial and operational decisions.<br>