Progettazione di un sistema proattivo per l'identificazione di aggregati

Nel lavoro di tesi è stato studiato il problema del tuning di un data warehouse, in particolare la tecnica maggiormente utilizzata in ambito aziendale, ovvero la creazione degli aggregati. Inoltre, è stato progettato e implementato uno strumento che generi automaticamente l'insieme di viste che meglio risolve il carico di lavoro basato sulle analisi di business più frequenti su quella specifica base di dati.

Data mining languages for business intelligence

Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

Integração da área de negócio de retalho do grupo Riopele no Data Warehouse corporativo

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Agile modeling data warehouse development

Most of the traditional software and database development approaches tend to be serial, not evolutionary and certainly not agile, especially on data-oriented aspects. Most of the more commonly used methodologies are strict, meaning they’re composed by several stages each with very specific associated tasks. A clear example is the Rational Unified Process (RUP), divided into Business Modeling, Requirements, Analysis & Design, Implementation, Testing and Deployment. But what happens when the needs of a well design and structured plan, meet the reality of a small starting company that aims to build an entire user experience solution. Here resource control and time productivity is vital, requirements are in constant change, and so is the product itself. In order to succeed in this environment a highly collaborative and evolutionary development approach is mandatory. The implications of constant changing requirements imply an iterative development process. Project focus is on Data Warehouse development and business modeling. This area is usually a tricky one. Business knowledge is part of the enterprise, how they work, their goals, what is relevant for analyses are internal business processes. Throughout this document it will be explained why Agile Modeling development was chosen. How an iterative and evolutionary methodology, allowed for reasonable planning and documentation while permitting development flexibility, from idea to product. More importantly how it was applied on the development of a Retail Focused Data Warehouse. A productized Data Warehouse built on the knowledge of not one but several client needs. One that aims not just to store usual business areas but create an innovative sets of business metrics by joining them with store environment analysis, converting Business Intelligence into Actionable Business Intelligence.

Modelação de um data warehouse para a Direcção Geral do Tesouro e Finanças e implementação de um data mart para o processo de gestão patrimonial.

Dissertação apresentada como requisito parcial para a obtenção do grau de Mestre em Estatística e Gestão da Informação

Business Intelligence -järjestelmä päätöksentekijöiden tukena asiantuntijayrityksessä

Työn tarkoituksena oli kartoittaa ja tehdä esiselvitys Business Intelligencen(BI) mahdollisuuksista tiedon hallinnassa. Tavoitteena oli selvittää, kuinka yritys voi tietotekniikan avulla paremmin hyödyntää operatiivisten järjestelmien tuottamia tietoja päätöksenteon tukena. Työssä sovellettiin konstruktiivista tutkimusotetta. Business Intelligence -teknologiaan tutustuttiin aluksi kirjallisuuden avulla. Ongelmaa lähestyttiin selvittämällä kohdeyrityksen tiedonhallinnan nykytila ja siihen liittyvät ongelmat. Käyttäjävaatimukset selvitettiin strukturoidulla kyselytutkimuksella. Lisäksi työn empiriaosuudessa tutustuttiin kahteen Business Intelligence -toteutukseen ja arvioitiin teknologian kypsyyttä suhteessa asiakasvaatimuksiin. Tiedonhallinnalta toivottiin joustavuutta ja helppokäyttöisyyttä.Erityisesti tutkimuksessa esiin nousi se, että tiedon jakeluun tarvitaan monipuolisempia vaihtoehtoja. Käyttäjät olivat valmiita hyödyntämään uusia BI-ominaisuuksia varsin laajalti. Haastavinta tutkimuksessa oli liiketoiminnan ymmärtäminen. Suurimmat BI-teknologian puutteet havaittiin loppukäyttäjän sovelluksissa. Tietovarastointiprosessiin liittyvä teknologia todettiin toimivaksi.

Construcció i explotació d'un magatzem de dades per a l'anàlisi d'informació sobre trànsit rodat de vehicles

Aquest document defineix la construcció i explotació d'un magatzem de dades per a la Fundació d'Estudis per a la Conducció Responsable. L'objectiu del projecte és homogeneïtzar la informació que rep la fundació, des de diverses fonts i en diferents formats, consolidar-la en un únic magatzem de dades i habilitar eines que facilitin la seva explotació i anàlisi. La consecució d'aquestes fites és determinant perquè la direcció conegui l'evolució del trànsit rodat de vehicles a Catalunya i minimitzi el riscos en cas de qualsevol presa de decisions.

Sistemas de gestión para el control de la cadena de abastecimiento que apropie características de los cubos OLAP como marco de aplicación en una empresa colombiana del sector de alimentos.

Se basa en un análisis teórico de los sistemas de información como lo es el almacenaje de datos, cubos OLAP e inteligencia de negocios. Seguidamente, se hace un análisis de los sectores económicos de Colombia con un especial interés sobre el sector de alimentos, de esta manera conceptualizar la empresa sobre la cual este trabajo se enfocara. Se encontrará un análisis del caso de éxito Summerwood Corporation, el cual brindará una justificación para la propuesta final presentada a la empresa Dipsa Food, Pyme dedicada a la producción de alimentos no perecederos ubicada en la ciudad de Bogotá D.C –Colombia, la cual tiene gran interés en cuanto al desarrollo de nuevas tecnologías que brinden información fidedigna para la toma de decisiones

Exploração de dados para soluções de retalho em business intelligence

Dissertação de mestrado integrado em Engenharia de Gestão e Sistemas de Informação

Data management as a part of performance management: Case study about production reporting development project

Because of the increased availability of different kind of business intelligence technologies and tools it can be easy to fall in illusion that new technologies will automatically solve the problems of data management and reporting of the company. The management is not only about management of technology but also the management of processes and people. This thesis is focusing more into traditional data management and performance management of production processes which both can be seen as a requirement for long lasting development. Also some of the operative BI solutions are considered in the ideal state of reporting system. The objectives of this study are to examine what requirements effective performance management of production processes have for data management and reporting of the company and to see how they are effecting on the efficiency of it. The research is executed as a theoretical literary research about the subjects and as a qualitative case study about reporting development project of Finnsugar Ltd. The case study is examined through theoretical frameworks and by the active participant observation. To get a better picture about the ideal state of reporting system simple investment calculations are performed. According to the results of the research, requirements for effective performance management of production processes are automation in the collection of data, integration of operative databases, usage of efficient data management technologies like ETL (Extract, Transform, Load) processes, data warehouse (DW) and Online Analytical Processing (OLAP) and efficient management of processes, data and roles.

Ensuring the efficient utilization of Business Intelligence

In recent years, chief information officers (CIOs) around the world have identified Business Intelligence (BI) as their top priority and as the best way to enhance their enterprises competitiveness. Yet, many enterprises are struggling to realize the business value that BI promises. This discrepancy causes important questions, for example: what are the critical success factors of Business Intelligence and, more importantly, how it can be ensured that a Business Intelligence program enhances enterprises competitiveness. The main objective of the study is to find out how it can be ensured that a BI program meets its goals in providing competitive advantage to an enterprise. The objective is approached with a literature review and a qualitative case study. For the literature review the main objective populates three research questions (RQs); RQ1: What is Business Intelligence and why is it important for modern enterprises? RQ2: What are the critical success factors of Business Intelligence programs? RQ3: How it can be ensured that CSFs are met? The qualitative case study covers the BI program of a Finnish global manufacturer company. The research questions for the case study are as follows; RQ4: What is the current state of the case company’s BI program and what are the key areas for improvement? RQ5: In what ways the case company’s Business Intelligence program could be improved? The case company’s BI program is researched using the following methods; action research, semi-structured interviews, maturity assessment and benchmarking. The literature review shows that Business Intelligence is a technology-based information process that contains a series of systematic activities, which are driven by the specific information needs of decision-makers. The objective of BI is to provide accurate, timely, fact-based information, which enables taking actions that lead to achieving competitive advantage. There are many reasons for the importance of Business Intelligence, two of the most important being; 1) It helps to bridge the gap between an enterprise’s current and its desired performance, and 2) It helps enterprises to be in alignment with key performance indicators meaning it helps an enterprise to align towards its key objectives. The literature review also shows that there are known critical success factors (CSFs) for Business Intelligence programs which have to be met if the above mentioned value is wanted to be achieved, for example; committed management support and sponsorship, business-driven development approach and sustainable data quality. The literature review shows that the most common challenges are related to these CSFs and, more importantly, that overcoming these challenges requires a more comprehensive form of BI, called Enterprise Performance Management (EPM). EPM links measurement to strategy by focusing on what is measured and why. The case study shows that many of the challenges faced in the case company’s BI program are related to the above-mentioned CSFs. The main challenges are; lack of support and sponsorship from business, lack of visibility to overall business performance, lack of rigid BI development process, lack of clear purpose for the BI program and poor data quality. To overcome these challenges the case company should define and design an enterprise metrics framework, make sure that BI development requirements are gathered and prioritized by business, focus on data quality and ownership, and finally define clear goals for the BI program and then support and sponsor these goals.

Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.