As with many new technology implementations before, Business Intelligence (BI) implementations have come under scrutiny in terms of the value added to organisations. The latest academic research uses various different ‘traditional financial methods’ such as the Return on Investment (ROI) calculations to determine the value of investments. In some instances customized measurement tools are proposed as a result of empirical studies conducted. The main objective of this study is to perform qualitative investigation on the theoretical value of BI implementations in organisations. If it is assumed that BI does add value to organisations, the primary research question aims to investigate how this value is added. A balanced scorecard second generation approach is used as theoretical framework in order to address the question. This approach is also known as strategy mapping. The research process starts with an extensive literature review on the topic of BI value evaluations and BI related balanced scorecards and strategy maps. As a result, various theoretical and practical research contributions are produced. One of the theoretical contributions includes an inventory of previous academic literature on the topic of BI value evaluations. This inventory is also presented diagrammatically. A preliminary version of the BI balanced scorecard is developed and used as foundation for a semi-structured interview template to investigate the value of BI in organisations.\ The semi-structured interview template was used as primary data generation instrument to gather data for this multiple-case study project. Four organisations participated in the study. The data obtained from the study was analysed and presented using an updated version of the theoretical framework of the study and was labelled as the intermediate version of the scorecard. The intermediate version of the BI balanced scorecard provided valuable input towards investigating how value was achieved as a result of BI implementations. These results were verified as part of a final verification process through a consultation process with the same study participants. A final version of the BI balanced scorecard is presented and included in a complete BI value solution. This version of the balanced scorecard is also a valuable practical contribution of the study. The verified results of the investigation indicated the following:- (1) BI adds value to organisations in all four perspectives of the organisation, namely the business value perspective, user orientation perspective, operational excellence perspective as well as the future orientation perspective. (2) Furthermore, the study confirmed that BI adds value to organisations through a number of benefits including an increase in sales and compliance to regulatory requirements (to name a few). (3) However, the study also indicated that value-related studies must adopt a holistic approach in an attempt to cater for the many facets of the topic. (4) Despite the challenge of implementing BI in organisations, the perceived value of BI implementations amongst senior management remained positive. This was supported by the continuous implementation of new BI projects in organisations. (5) There was a definite relationship between BI implementations and organisational performance. This is evident through the positive impact on sales figures, risk and compliance management and operational management. The study contributes to the broader field of Information Systems (IS) in numerous ways. Firstly the research discovers gaps in existing research, then proposes a method to investigate the research question as a result of the gaps identified, and -iiiuses this method as a tool to investigate the problem. The main contribution of the study is to contribute to the body of knowledge by investigating the value of business intelligence to organisations. / College of Engineering, Science & Technology / D. Litt et. Phil. (Information Systems)

Dagens konkurrensutsatta marknad ställer stora krav på organisationer och deras användning av hjälpmedel för att överleva och skapa konkurrensfördelar. Business intelligence är en samlingsteknik som för varje dag får allt större uppmärksamhet och som för många organisationer blivit ett måste för överleva. Tyvärr är implementationen av BI-tekniker problematisk och över 50 % av alla BI-initiativ misslyckas. Därför har en del studier forskat kring de kritiska framgångsfaktorerna för implementation av BI, som anses som en nyckel för att lyckas med implementationen. I den stora majoriteten av studierna utgår de kritiska framgångsfaktorerna dock från stora företag. De har andra förutsättningar än små och medelstora företag (SMF) som 99.9% av alla företag i Sverige består av. Studien har därför skapat en ram med kritiska faktorer speciellt uttagna för SMF med frågeställningen: Vilka är de kritiska framgångsfaktorerna för implementation av ett business intelligence system i SMF? Ramen skapades med litteraturstudie i kombination med expertintervjuer. Studiens ram visar att faktorerna inte skiljer sig nämnvärt efter företagsstorleken, utan efter projektets storlek. Nyckelord: Business intelligence, Kritiska framgångsfaktorer, Implementation, Små och medelstora företag / Today’s competitive market places great demands on organisations and their use of means to survive and gain competitive advantages. Business intelligence (BI) is an umbrella term of technologies that has become necessary for many organisations to survive the competitive market, and it gets more attention for every passing day. Unfortunately, the implementation of BI technologies is problematic and statistics show that more than 50% of all BI-initiatives fail. Therefore, some studies have identified critical success factors (CSFs), crucial for the implementation of BI, which is considered as a key for the success of a BI-project. However, the majority of the CSFs are based on large, international enterprises. Which differ from small and medium-sized enterprises (SMEs) which 99.9% of all Swedish companies consist of. Thus are the identification of relevant CSFs for SMEs crucial. The study has therefore with the research question: Which are the CSFs for implementation of BI-systems in SMEs created a framework with CSFs specially designed for SMEs, based on a literature review combined with expert interviews. The analysis and result of the study shows that the CSFs do not differ in terms of the organisation size, rather it differs depending on the size of the project. However, the study has also identified previously unidentified critical success factors crucial for the implementation of BI-systems. Keywords: Business intelligence, Critical Success factors, Implementation, Small and medium-sized enterprises

Vor dem Hintergrund der Zunahme unstrukturierter Daten für Unternehmen befasst sich dieser Beitrag mit den Möglichkeiten, die durch den Einsatz der Business Intelligence für Unternehmen bestehen, wenn durch gezielte Analyse die Bedeutung dieser Daten erfasst, gefiltert und ausgewertet werden können. Allgemein ist das Ziel der Business Intelligence die Unterstützung von Entscheidungen, die im Unternehmen (auf Basis strukturierter Daten) getroffen werden. Die zusätzliche Auswertung von unstrukturierten Daten, d.h. unternehmensinternen Dokumenten oder Texten aus dem Web 2.0, führt zu einer Vergrößerung des Potenzials und dient der Erweiterung des Geschäftsverständnisses der Verbesserung der Entscheidungsfindung. Der Beitrag erläutert dabei nicht nur Konzepte und Verfahren, die diese Analysen ermöglichen, sondern zeigt auch Fallbeispiele zur Demonstration ihrer Nützlichkeit.

Automotive SPICE is used to evaluate the efficiency of the development processes for OEMs and ECU suppliers. It is a domain specific version of SPICE. Many automotive manufacturers are demanding Automotive SPICE level 2 from their suppliers. Application life cycle management solutions specific to automotive industry focus more on standardisation yet providing very little information about performance of processes. This thesis shows how Business Intelligence (BI) solutions can be helpful in achieving Automotive SPICE level 2 compliance and as comprehensive reporting tools. Moreover the evaluation of approaches for implementation of different BI systems has shown that commercial solutions can be beneficial for small to medium size suppliers. Implementing a BI solution can also point out possible improvement opportunities and bad practices for an organisation. The implemented BI system can only be efficient and useful if the underlying data is accurate and responsive.

The Swedish   healthcare system today has longer queues than before, low treatment rates   and lack of accessibility, treatment and service. Business Intelligence   System (BIS) purpose is to support organizations and businesses in different   types of decision-making that in turn can make the operations more efficient.   The purpose of this thesis is to develop and test a model that describes the   effects that BIS have on the healthcare system according to previous research   on Swedish healthcare staff and their experiences of these systems. The study   has been carried out through qualitative interviews with respondents who work   with BIS in the Swedish healthcare system. A model developed from previous   research has according to the purpose of this study been developed and tested   against the collected empirical data to see if the effects that the previous   research has identified are in line with what Swedish healthcare staff has identified.   The entire model which consists of BIS basic functionality and BIS effects on   healthcare has been tested against another respondent who did not participate   on any interview but instead performed a thorough analysis of the whole   model. What were tested by this respondent were the model’s flow, structure   and constituents. The result of this study came to the conclusion that the   basic functionality of the model developed and the identified effects are in   accordance with the effects identified by the Swedish healthcare staff they   receive from the BIS within their work. / Sammanfattning: Den svenska sjukvården har idag längre köer än   tidigare, låg behandlingstakt och brister i tillgänglighet, bemötande och   service. Business Intelligence System (BIS) har som syfte att stödja   organisationer och verksamheter vid olika typer av beslutstaganden som i sin   tur kan effektivisera verksamheten. Syftet med detta examensarbete är att   utveckla och testa en modell som beskriver de effekter som BIS har på   sjukvården enligt tidigare forskning mot svensk sjukvårdspersonal och deras   upplevelser utav dessa system. Studien har utförts genom kvalitativa   intervjuer med respondenter som arbetar med BIS inom den svenska sjukvården.   En modell som bygger på tidigare forskning har enligt syftet i denna studie   utvecklats och testats mot den insamlade empirin för att se om de effekter   som den tidigare forskningen har identifierat stämmer överens med vad svensk   sjukvårdspersonal har identifierat. Hela modellen som består av BIS   grundläggande funktionalitet samt BIS effekter på sjukvården har sedan   testats mot ytterligare en respondent som inte deltog i någon intervju utan   endast analyserat modellens helhet. Det som testades av denna respondent var   modellens flöde, struktur och beståndsdelar. Resultatet av denna studie kom   fram till att den framtagna modellens grundläggande funktionalitet samt de   effekter som återfinns i modellen stämmer överens med de effekter som den   svenska sjukvårdspersonalen har identifierat att de får ut av BIS inom sitt   arbete.,

I dagens affärsvärld är det i princip ett måste för verksamheter att ta del av den konkurrensfördel som Jinns möjlig via att använda affärsdata genererat av en verksamhets processer för att sedan ta eventuella beslut, detta möjliggörs inom en Business Intelligence- miljö. Dock behöver dessa beslut ofta tas snabbare, mer nu än förr, detta sätter allt större press på den IT-avdelning som skall tillhandahålla beslutsfattare det beslutsunderlag som är nödvändig. På grund av nödvändigheten för dom snabba besluten behöver verksamheter korta ner dom ledtider som den traditionella Business Intelligence-miljön skapar. Ledtiderna skapas via att en beslutsfattare skapar en förfrågan på en analys och IT-avdelningen sedan tar fram en rapport som kan svara på förfrågan. För att verksamheter tillsammans med IT-avdelningen skall kunna minska ledtider kan verksamheten införa en så kallad Self-Service BI-miljö[SSBI]. SSBI fokuserar mer på att göra beslutsfattare självständiga genom att möjliggöra för beslutsfattare att själva, utan hjälp av en IT-avdelning ta del av data och analysera data för att ta sina eventuella beslut. Verksamheter lyckas inte alltid med att införa SSBI, det har visat sig Jinnas många stora utmaningar med ett sådant införande. Att tillgängliggöra data för beslutsfattare inom en sådan miljö är en del av alla utmaningar, men vad Jinns det för utmaningar inom just tillgängliggörandet? Vilka faktorer bör verksamheter fokusera på vid tillgängliggörandet av data, detta är frågor som denna studie skall besvara. Studien baseras på frågeformuleringen nedan: • Hur bör data tillgängliggöras till slutanvändare vid införande av SSBI? Studien genomförs via en fallstudie som involverar ett Jlertal intervjuer av respondenter anställda på ett ledande företag inom Sverige som konsulterar stora verksamheter att inom Business Intelligence och dessutom Self-Service BI. En litteraturgranskning av forskning inom samma domän sker också under studiens gång för att skapa en grund inför intervjuerna. Samt också berika informationen från respondenterna. Resultatet av studien är en modell med diverse faktorer och utmaningar med tre huvudkategorier med tillhörande underkategorier som verksamheter bör fokusera på vid tillgängliggörande av data i en SSBI-miljö. / In today's business world, in fact, it is a must for businesses to take part of the competitive advantage that is made possible by using business data generated by a business's processes and then taking decisions, this is made possible within a Business Intelligence environment. However, these decisions often need to be taken more quickly, more now than before, this is putting increasing pressure on the IT department to provide decision makers with the necessary supporting documentation. Due to the necessity for the quick decisions, businesses need to shorten the lead times that an traditional Business Intelligence environment creates. This is because a decision maker creates an inquiry for an analysis and the IT department then produces a report that can respond to the request. In order for businesses to be able to reduce lead times together with the IT department, the company can introduce a so-called Self- Service BI environment [SSBI]. SSBI focuses more on making decision makers self-reliant by enabling decision makers to themselves, without the help of an IT department, to analyze data to make their decisions. Businesses do not always succeed in introducing SSBI, it has proved to be many major challenges with such introduction. Making data available to decision makers in such an environment is one part of all the challenges, but what are the challenges in the area of accessibility? What factors should businesses focus on when making data available, these are questions that this study answer. The study is based on the question below: • How should data be made available to end users when introducing SSBI? The study is carried out by a case study that involves a number of interviews of respondents employed at a leading company in Sweden that consult large businesses within Business Intelligence and also Self-Service BI. A literature review of research within the same domain also takes place during the study to enrich the information from the respondents. The result of the study is a model with various factors and challenges with three main categories with associated subcategories that businesses should focus on when making data available in an SSBI environment.

Data warehouse har länge varit, och är fortfarande, en viktig tillgång för organisationer för att lagra data för analys. Under det senaste årtionde har en exponentiell ökning av data skett, vilket givit organisationer allt större möjligheter att fatta datadrivna beslut i en helt ny utsträckning. Likväl har det i många fall även satt press på organisationer att utnyttja data som en tillgång för att reagera och ta tillvara på möjligheter i ett hårdnande affärsklimat, eller rent av för att bibehålla konkurrenskraft. För att möjliggöra för organisationer att kunna reagera i tid ställs flexibilitetskrav på de tekniker som används för att hantera data för analys. Praxis som länge rått för data warehouse spås inom kort inte längre vara aktuellt. Organisationer behöver hitta nya vägar för att snabbt lyckas ställa om och anpassa sig efter marknadens behov. Många organisationer har i dagsläget ett traditionellt data warehouse, och denna studie undersöker hur väl data virtualization kan bidra till att öka flexibiliteten genom att adderas som ett komplement. Detta undersöks genom frågeställningen:Hur kan data virtualization komplettera och förbättra ett traditionellt data warehouse?För att besvara frågeställningen genomförs en litteraturanalys och en fallstudie följt av en implementation, där datainsamlingen primärt består av tester utförda utifrån implementationsresultatet, observationer och intervjuer.Resultatet visar på en delad bild, där utförda tester potentiellt kan ses ifrågasätta delar av intervjuresultatet och befintlig litteratur. Utifrån resultatet kan en del konstateranden göras om i vilka användningsfall data virtualization inte passar, samt ge en bild av när det kan vara ett alternativ. Data virtualization bör ses som en utbyggnad av ett data warehouse som möjliggör sammansättning, transformering och beräkning av data, där datastrukturer kan ändras när som helst. En organisation som anammar denna flexiblare lösning måste dock vara beredda på rejält höjda svarstider för att utvinna data. / Data warehouse has for a long time been, and still is, an important asset for organizations to store data for analysis. In the last decade, an exponential increase in data has taken place, giving organizations increasingly greater opportunities to make data-driven decisions in completely new ways. Nevertheless, in many cases, it also puts pressure on organizations to use data as an asset to react and take advantage of opportunities in a harder business climate, or even to maintain competitiveness. In order to enable organizations to be able to react in time, flexibility requirements are imposed on the techniques used to handle data for analysis. The traditional best practices for data warehouse is predicted to soon be out of date. Organizations need to find new ways to quickly change and adapt to the needs of the market. Many organizations currently have a traditional data warehouse, and this study examines how well data virtualization can help increase flexibility by being added as a complement. This is examined through the question:How can data virtualization complement and improve a traditional data warehouse?To answer this question, a literature analysis, and a case study followed by an implementation is carried out, in which the data collection consists primarily of tests performed on the implementation result, observations and interviews.The result shows a divided picture, where performed tests can potentially be seen as questioning parts of the interview results and existing literature. Based on the result, some findings can be made about in which use-cases data virtualization does not fit, and gives a picture of when it can be an alternative. Data virtualization should be seen as an extension of a data warehouse that enables the federation, transformation and computation of data, where data structures can be changed at any time. However, an organization that embraces this more flexible solution must be prepared for substantially increased response times in data extraction.

Sistemas educacionais possuem diversas funcionalidades capazes de apoiar a interação entre alunos e professores de maneira dinâmica, síncrona e assíncrona. Uma das formas de monitorar a eficácia do processo educacional e por meio da utilização dos dados armazenados nesses sistemas como fonte de informação. Pesquisas em Learning Analytics, Academic Analytics e Mineração de Dados Educacionais, buscam explorar os dados de sistemas educacionais utilizando processamento analítico e técnicas de mineração de dados. No entanto, há uma serie de fatores que dificultam a gestão eficiente do processo educacional a partir dos dados de sistemas educacionais. A transformação de dados provenientes de diferentes tipos de sistemas educacionais, como Sistemas de Gestão de Aprendizagem e Sistemas Acadêmicos, e uma tarefa complexa devido a natureza heterogênea dos dados. Dados provenientes desses sistemas podem ser analisados considerando diferentes stakeholders, sob varias perspectivas e níveis de granularidade. Neste cenário, um modelo de referência para a descoberta de conhecimento a partir de dados de sistemas educacionais, denominado Modelo de Referência de Dados Educacionais (EDRM), foi desenvolvido neste trabalho. O EDRM e um modelo dimensional no formato star schema, estruturado em um Data Warehouse, projetado para ser uma fonte única de dados integrados e correlacionados voltada a tomada de decisão. Assim, e possível armazenar dados de diversas fontes, combina-los e, por fim, realizar analises que levem as instituições a desenvolver uma melhor compreensão, rastrear tendências e descobrir lacunas e ineficiências acerca do processo educacional. Neste trabalho, o EDRM foi validado por meio de um estudo de caso, utilizando bases de dados reais coletadas de diferentes sistemas educacionais. Os resultados mostram que o EDRM e eficiente em tarefas com diferentes objetivos, utilizando processamento analítico e mineração de dados. / Educational systems support dynamic, synchronous and asynchronous interaction between students and educators. Researches in Learning Analytics, Academic Analytics and Educational Data Mining explore data from educational systems for knowledge discovery through analytical processing, statistical analysis and data mining. However, there are some factors that hinder an efficient management of the educational process. The transformation of data from different kinds of educational system, as Learning Management Systems and Student Information Systems, can be even more difficult due to data heterogeneity. Data from these systems can be analyzed considering different stakeholders, under different perspectives and under different granularities. Motivated by this scenario, in this work we propose Modelo de Referência de Dados Educacionais (EDRM), a reference data model for knowledge discovery in data from educational systems. EDRM is an analytical model structured under a Data Warehouse architecture following a multidimensional data model. EDRM is projected for being an resource of integrated and correlated data focused in decision taking in the educational process. EDRM was developed considering a deep analysis of data and functionalities from different educational systems. In this sense, data from different kinds of systems and sources can be used unified, integrated and consistently. This allows institutions to better comprehend their data, as well as discover patterns, gaps and inefficiencies about their educational process. In this work, EDRM was validated in a case study using real-world databases from different educational systems. The results indicate that EDRM is efficient in tasks with different objectives, using Learning Analytics and Educational Data Mining techniques, and analyzing different perspectives.

A evolução pela qual passou o chão-de-fábrica no último século transformou-o numa área estratégica para as empresas, por meio da qual é possível atender e satisfazer as necessidades dos seus clientes. Esse novo chão-de-fábrica gera hoje uma grande quantidade de dados nos controles do seu processo produtivo, os quais, em muitos casos, após seu uso imediato ou de curto prazo, acabam descartados ou armazenados inadequadamente, impossibilitando ou dificultando seu acesso. Esses dados, no entanto, podem vir a ter uma importante utilidade como matéria-prima para a geração de informações úteis à gestão do negócio. Aliado à necessidade que as empresas hoje têm de possuir um adequado sistema de medição de desempenho, é possível obter, a partir dos dados históricos do chão-de-fábrica, um bom conjunto de indicadores de desempenho para a área. Para isso, esses dados precisam ser modelados em sistemas especialmente projetados para esta função. Esses sistemas vêm sendo tratados como sistemas de apoio à decisão (SAD) ou Business Intelligence (BI). Como solução para os problemas acima, foi feita então uma revisão sobre os temas: sistemas de informação, ERP, sistemas de medição de desempenho, qualidade da informação, SAD/BI, bem como uma revisão sobre os trabalhos científicos relacionados ao tema da tese. Uma vez tendo sido esses conceitos consolidados, partiu-se para o desenvolvimento de um modelo dimensional de BI que se utilizou das ferramentas de Data Warehouse, On Line Analytical Processing (OLAP) e Data Mining. O software utilizado foi o Analysis Services, pertencente ao banco de dados Microsoft SQL Server 2000. Em seguida, o modelo foi testado com dados reais de uma empresa do ramo metal-mecânico, tratada aqui como “empresa A". Por meio do modelo e dos dados reais, uma série de análises foram realizadas com o intuito de mostrar a contribuição, capacidade, flexibilidade e facilidade de uso do modelo, atingindo o objetivo proposto / The shop floor evolution in the last century has transformed it in a strategic area for the companies, through which is possible to reach and to satisfy the customers needs. This new shop floor generates today a great amount of data by the productive process controls, the ones which, in many cases, after its immediate use or in a short period, are discarded or stored inadequately, disabling or making impossible its access. These data, however, can come to have an important use as raw material for the production of useful information to the business administration. Together to the need that the companies have today to possess an appropriated performance measure system, it is possible to obtain, from the historical shop floor data, a good performance indicators group for the area. For that, these data must be modeled by systems specifically designed for this purpose. These systems have been treated as decision support systems (DSS) or Business Intelligence (BI). As solution for the problems above, it was made a review over the following themes: information systems, ERP, performance measure system, information quality, DSS/BI, as well as a review about the scientific works related to this thesis theme. Once consolidated these concepts, started the development of a BI dimensional model, that used Data Warehouse tools, On Line Analytical Processing (OLAP) and Data Mining. It was used the Analysis Services software, belonged to the Microsoft SQL Server 2000 database. In the following, the model was tested with real data from a metal-mechanic company branch, called here as “company A". Through the model and of the real data, a series of analyses was accomplished with the intention of showing the model contribution, capacity, flexibility and use easiness, reaching the proposed objective

Made available in DSpace on 2015-03-05T19:12:39Z (GMT). No. of bitstreams: 0 Previous issue date: 16 / Nenhuma / O objetivo dessa pesquisa é propor um modelo de apoio informacional metodológico (MAIM) que atenda as principais necessidades da auditoria interna de uma instituição privada de ensino superior, com o uso de Business Intelligence. Realizou-se uma pesquisa qualitativa que permitiu um estudo em uma instituição privada de ensino superior localizada na região Metropolitana de Porto Alegre. Por meio de entrevistas com o Pró-Reitor de Administração e com os Auditores Internos da instituição, foi possível estruturar Etapas Metodológicas para a configuração do modelo proposto, em consonância com as Normas de Auditoria Interna. Do estudo realizado pode-se concluir que, apoiada no modelo informacional proposto, a auditoria interna tem condições de identificar prioridades no seu programa de trabalho, à luz dos planos e metas estratégicas da instituição, de tal forma que o auditor interno pode definir procedimentos operacionais para trabalhar em prol do alcance dos objetivos da organização / The objective of this research is to consider a model of informational methodology support model (IMSM) that takes care of the main necessities of the internal auditorship of a private institution of superior education with the use of Business Intelligence. A qualitative research that permited a study in a private institution of superior education located in the region Metropolitan of Porto Alegre, where, by means of interviews with the pro-reitor of administration and with the internal auditors of the institution, it was possible to structuralize methodological stages for the construction of the considered model, according to the rules of internal auditorship. Of the carried through study it can be concluded that, supported in the considered informational model, the internal auditorship has conditions to identify priorities in its program of work, to the light of the plans and strategical goals of the institution, of such form that the internal auditor can define operational procedures to work in favor of th