The theme of this thesis is to pave a path to vertically extract business intelligence (BI) from software code to business intelligence base, which is a tank of BI. Business intelligence is the atomic unit to build a piece of program comprehensibility in business logic point of view. It outstands because it covers all reverse engineering levels from code to specification. It refers to technologies for the localisation, extraction, analysis of business intelligence in software system. Such an approach naturally requires information transformation from software system to business intelligence base, and hence a novel set of automatic business intelligence recovery methods are needed. After a brief introduction of major issues covered by this thesis, the state of art of the area coined by the author as “business intelligence elicitation from software system”, in particular, the kinds of business intelligence that can be elicited from software system and their corresponding reverse engineering technical solutions are presented. Several new techniques are invented to pave the way towards realising this approach and make it light-weight. In particular, a programming-style-based method is proposed to partition a source program into business intelligence oriented program modules; concept recovery rules are defined to recover business intelligence concepts from the names embedded in a program module; formal concept analysis is built to model the recovered business intelligence and present business logic. The future research of this task is viewed as “automating business intelligence accumulation in Web” which is defined to bridge work in this thesis to nowadays Web computing trends. A prototype tool for recovering business intelligence from a Web-based mobile retailing system is then presented, followed by case study giving evaluation on the approach in different aspects. Finally, conclusions are drawn. Original contributions of this research work to the field of software reverse engineering are made explicit and future opportunities are explored.

Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportunities to make an organisation more competitive by allowing manager to make more informed decisions and as a result, corporate resources optimally utilised. This potential insight provides organisations with an unrivalled opportunity to remain abreast of market trends. Consequently, BI techniques provide significant opportunity for integration with Decision Support Systems (DSS). The gap which was identified within the current body of knowledge and motivated this research, revealed that currently no suitable framework for BI, which can be applied at a meta-level and is therefore tool, technology and domain independent, currently exists. To address the identified gap this study proposes a meta-level framework: - ‘KDDS-BI’, which can be applied at an abstract level and therefore structure a BI investigation, irrespective of the end user. KDDS-BI not only facilitates the selection of suitable techniques for BI investigations, reducing the reliance upon ad-hoc investigative approaches which rely upon ‘trial and error’, yet further integrates Knowledge Management (KM) principles to ensure the retention and transfer of knowledge due to a structured approach to provide DSS that are based upon the principles of BI. In order to evaluate and validate the framework, KDDS-BI has been investigated through three distinct case studies. First KDDS-BI facilitates the integration of BI within ‘Direct Marketing’ to provide innovative solutions for analysis based upon the most suitable BI technique. Secondly, KDDS-BI is investigated within sales promotion, to facilitate the selection of tools and techniques for more focused in store marketing campaigns and increase revenue through the discovery of hidden data, and finally, operations management is analysed within a highly dynamic and unstructured environment of the London Underground Ltd. network through unique a BI solution to organise and manage resources, thereby increasing the efficiency of business processes. The three case studies provide insight into not only how KDDS-BI provides structure to the integration of BI within business process, but additionally the opportunity to analyse the performance of KDDS-BI within three independent environments for distinct purposes provided structure through KDDS-BI thereby validating and corroborating the proposed framework and adding value to business processes.

Business intelligence (BI) systems comprise one of the largest and fastest growing areas of IT expenditure in companies today. Companies’ experiences with deriving benefits from these systems are still mixed. One of the differences between BI and other types of information systems is that how BI systems are used, not just whether they are used, can have a major impact on the benefits derived. Therefore the characteristics of BI users and the organizations within which they work can have a disproportionate impact on the benefits derived from investments in BI. Organizational competence is one way to evaluate the characteristics of individuals and organizations relative to their ability to achieve organizational goals. This dissertation examines the characteristics of BI users and their organizations within the framework of organizational competences. Models representing those competences at both the individual and organizational level are presented. A combined competency model and resulting emerging competences are proposed that, if adopted, can improve the likelihood of organizations realizing benefits from their BI investments.

Due to the rapid growth of new technologies, the Business Intelligence (BI) market is growing as well that forces the corporations to adopt their offerings to the needs of the customer. Adoption of Business Intelligence system has become one of the most important technological and organizational innovations in modern organization that promote knowledge diffusion, and cornerstone of business decision making processes. Since the way of BI integrated and implemented is quite different among organizations, it is important to approach BI literature by adaption of BI application and its implementation, BI architects, and enabling factors in BI projects. Furthermore, we are also going to discuss how technological capabilities such as user access, data quality and the integration of BI with other systems in the firm, as well as organizational capabilities such as flexibility and risk management support, are essential for BI success, regardless of the decision environment. Last but not least, this paper will also discuss how the idea of BI has been built on the school of thought. We expect that results could create the value and input for enterprises that plan to implement a BI application in their organization.

Companies in these days deal with underlying issue that concerns about questions how to manage volume growth of corporate data needed to decision making processes and how to control credibility and relevance of derived information and knowledge. Other questions deal with problem of responsibility and data security that represents potential risk of information outflow. The Data Governance concepts provide comprehensive answer to these questions. However, making a decision on implementing a Data Governance program is usually triggering many other problems like setting up environments, making determination of project scope, allocating capacity of data experts and finding one's way in non-uniform Data Governance concepts offered by various IT vendors. The aim of this thesis is to draw the unified and universal implementation process that helps with setting up DG projects and makes certain conception about how to run these projects step-by-step. The first and the second part of the thesis are dedicated to describe principles, components and tools of Data Governance and also methods of measuring data quality levels. The third part is offering concrete approach for successful implementation of Data Governance conception into corporate data environment.

In this thesis, the issue which is discussed applies to effects of Business Intelligence (BI). They are described in more detail the benefits and potential use of BI in various application areas, namely finance, marketing, manufacturing, logistics, supply chain management, human resources, CI, web analytics, informatics, and CPM. There are a lot of effects which BI brings. They are divided into different categories, which are the effects of economic, customer, personnel and increasing the analytical process and performance. BI provides many benefits to all of mentioned application areas. But in each of them it may occurs some problems which may involves the introduction of BI into different areas. The main goal is to review the possibilities of planning and analysis of BI effects. I would like to make the readers acquainted with effects which are brought together with BI applications, with the structure based on the application areas and based on the categories mentioned here. All of the effects are collected from the case studies and others sources mentioned in the end. The main contribution is the unified view to the effects which brings the implementation of BI to the enterprise. At each of the effects are mentioned the main dimensions needed to monitor during analysis, and importance to the enterprise during its planning. This thesis can be used as a basis for the next topics connected with the effects of BI or with the application areas.

This thesis deals with the area of Business Intelligence and especially the part of data quality. The goal is provide an overview of data quality issue and possible ways the data can be shown to have better and more engaging informative value. Another goal was to make a proposal solution to the visualization of the system state, particularly the section of data quality, at the concrete enterprise. The output of this thesis should provide a quideline for the implementation of the proposed solution.

Small, medium and micro enterprises (SMMEs) face significant challenges that include resource scarcity and information asymmetry (when competing with larger well-established firms), and the general problems associated with making timely, market-aware strategic decisions. SMMEs may be able to improve their firm performance by copying aspects of corporate entrepreneurship, such as cooperative corporate venturing, and by adopting of technological innovations such as the use of business intelligence. These are initiatives that are typically utilised by large well-established firms; however, SMMEs should derive similar benefits from cooperative corporate venturing and business intelligence, as would larger well-established firms. This study sought to determine the relevance of business intelligence and cooperative corporate venturing in the operation of small, medium and micro enterprises and the relation thereof to the economic performance of these firms, as perceived by the owner-managers of the firm. The study was performed by examining the perceived impact that the strategic initiatives, (namely business intelligence and cooperative corporate venturing) would have on SMME firm economic performance, from the perspective of owner-managers of the firm who participated in the survey. Quantitative data was obtained through a self-administered questionnaire, which was distributed electronically to SMMEs whose email addresses were found online, and physically to individuals attending forums (and workshops) for SMMEs and entrepreneurs; companies operating in and around industrial parks and villages; and, members of the Wits business school community. It was shown in this study that there is indeed a relationship between the adoption of cooperative corporate venturing and the perceived level of SMME firm performance. Ample research has not been conducted that focuses on the hybrid strategy of business intelligence and cooperative corporate venturing on SMME firm performance. This is area of research that potentially benefits SMMEs, and both academic and business intelligence stakeholders.

Det har blivit viktigare för organisationer att utnyttja data i sina verksamheter allt eftersom konkurrenterna blir bättre och bättre på att ta beslut med hjälp av data. Därför har frågeställningen uppkommit vilka faktorer som är viktigast vid ett införande av en datadriven kultur. Studien har gått igenom vad litteraturen säger om vilka faktorer som är viktiga vid ett införande av en datadriven kultur där en modell togs fram för att illustrera de områden som ingår. Enligt litteraturstudien framstod områdena management, data, kultur och verktyg som viktigast vid ett införande med en extra stor viktning på management. Intervjuerna gjordes med ett konsultbolag om sammanlagt tre intervjuer som kom fram till att de viktigaste faktorerna var management, data och kultur med en exkludering för verktyg då de ansåg att typen av verktyg är oviktiga.

Performance analysis är ett väldigt diskuterat ämne, den kan användas i samband med alla sporter och användningen utav det har blivit mycket populär den senaste tiden.Fotbollsorganisationer runt om i världen använder sig av det i samband med träningar och matcher för att utveckla sina spelare men även laget i helhet. Syftet med denna studie är att undersöka hur elit-fotbollslagen i Göteborgsregionen använder sig av performance analysis i kombination med träningar och matcher.Frågeställningen som denna undersökning har som syfte att besvara är:Fråga 1.”Hur används business intelligence/performance analysis inom fotboll och hur tillämpas det inom elitfotbollen i Göteborgsregionen? ”För att besvara frågeställningen tillämpas två olika datainsamlingsmetoder, en systematisk litteraturstudie och kvalitativa intervjuer. Detta för att få information från litteraturen om hur dessa två parter har kombinerats samt vilka fördelar och utmaningar som skapades vid kombinationen. Men även få en inblick om vad personer med kunskap om två parter tycker om en kombination, vad de tycker en kombination kan bidra till men också vilka utmaningar som kan förekomma med kombinationen.Undersökningen visar tydligt att det finns fördelar med att kombinera business intelligence/ performance analysis och fotboll. De fördelar som diskuteras kontinuerligt är bättre utveckling för fotbollsspelarna, möjligheten om att mäta spelarprestationen,bättre underlag för beslutsfattning. Det fanns fotbollslag som hade svårt med att införa nya system på grund av olika skäl som inte kunde mäta spelarprestationen. Att kombinera performance analysis och fotboll förstärker laget i helhet för att laget har tillräckligt med information när det handlar om spelarna och deras förutsättningar. Det bidrar till att fotbollslag kan träna upp spelare och utveckla spelare själva istället för att lägga miljonbelopp på andra spelare.