Den ökade mängden realtidsdata som bland annat IoT-utvecklingen för med sig gör business intelligence (BI) i realtid mer relevant än någonsin. Då många BI-projekt tenderar till att misslyckas är förståelse av kritiska framgångsfaktorer vitalt. Denna studie syftar till att undersöka vilka skillnader i kritiska framgångsfaktorer som utmärker implementationer av realtids-BI (RBI) system jämfört med BI-implementationer. Semistrukturerade intervjuer baserade på forskning kring framgångsfaktorer för BI har använts för att undersöka utmärkande drag för RBI. Studien har identifierat att RBI kräver en arkitektur designad för att stödja analys av strömmande data samt att RBI kräver ett mer visionärt och experimentellt förhållningssätt. Slutligen belyser studien att risken för feltolkning och felaktiga slutsatser ökar då beslut tas utifrån rådata. Därmed krävs en högre datakvalitet vid RBI för att data ska anses vara av en hållbar kvalitet. / The increased amount of real-time data, such as IoT's development, makes business intelligence (BI) in real-time more relevant than ever before. As many BI projects tend to fail, the understanding of critical success factors are vital. This study aims to investigate the differences in critical success factors that characterize implementations of real-time BI (RBI) systems versus BI implementations. Semi-structured interviews based on research of critical success factors for BI has been used to investigate distinguishing features for RBI. The study has identified that RBI requires an architecture designed to support analysis of streaming data and that a more visionary and experimental approach is required. Finally, the study highlights that the risk of misinterpretation and incorrect conclusions increases when decisions are taken based on raw data. Therefore, higher data quality is required to be considered to be a sustainable quality in the RBI context.

This work is focused on OLAP analysis. The work presents important theoretic facts and compares availible OLAP systems in different ways. The main goal was to create own OLAP system. Design and implementation of this system is described in the project.

Major cyber attacks against the cyber networks of organizations has become a common phenomenon nowadays. Cyber attacks are carried out both through the spread of malware and also through multi-stage attacks known as hacking. A cyber network can be represented directly as a simple directed or undirected network (graph) of nodes and arcs. It can also be represented by a transformed network such as the attack graph which uses information about network topology, attacker profile, and existing vulnerabilities to represent all the potential attack paths from readily accesible vulnerabilities to valuable target nodes. Then, interdicting or hardening a subset of arcs in the network naturally maps into deploying security countermeasures on the associated devices or connections. In this dissertation, we develop network interdiction models and algorithms to optimally select a subset of arcs which upon interdiction minimizes the spread of infection or minimizes the loss from multi-stage attacks. In particular, we define four novel network connectivity-based metrics and develop interdiction models to optimize the metrics. Direct network representation of the physical cyber network is used as the underlying network in this case. Two of the interdiction models prove to be very effective arc removal methods for minimizing the spread of infection. We also develop multi-level network interdiction models that remove a subset of arcs to minimize the loss from multi-stage attacks. Our models capture the defenderattacker interaction in terms of stackelberg zero-sum games considering the attacker both as a complete rational and bounded rational agents. Our novel solution algorithms based on constraint and column generation and enhanced by heuristic methods efficiently solve the difficult multi-level mixed-integer programs with integer variables in all levels in reasonable times.

Two trends that have become increasingly noticeable in recent years are increased data volumes and an increased focus on climate change. With an ever-increasing number of companies performing value-creating activities at the intersection of these two areas, and still relatively few previous studies, there is an interest in investigating how these two areas can be integrated. The purpose of the work is therefore to investigate the integration of sustainability data in Business Intelligence (BI) for companies in greentech, i.e. companies whose goal is to use technology to contribute to a more sustainable future. Based on this, guidelines and insights about good design and implications for the business are then generated. An interdisciplinary approach is utilized where accepted design theory, such as Donald Norman's design principles and the Action Design Research development framework, is combined with information systems and business intelligence theory. In practice, this has meant an iterative process where a prototype of a Business Intelligence tool has been developed to visualize sustainability data for a greentech company. The tool has been continuously evaluated by representatives from different parts of the company to investigate which factors are most important for high usability and what effects more easily accessible sustainability data has on the business. The investigation shows, among other things, that it is of great importance that the tool is closely aligned with the organization’s other activities, both in terms of design and daily operations, and that a highly requested functionality is the ability to segment and compare data in many ways. At the same time, there are several aspects that add complexity to the issue, such as a conflict between the organization and the employees as to whether Swedish or English should be the language of the tool. In addition, the results also indicate that a lack of easily accessible and accurate data can result in decisions being made based on intuition and experience, despite the advice of previous research. Something that also emerges clearly during the tests is the trend that an increasing number of companies need to report more sustainability information, and the area is therefore highly relevant for further research. / Två trender som blivit alltmer påtagliga de senaste åren är ökade datamängder och ökat fokus på klimatförändringar. Med ett ständigt växande antal företag som bedriver värdeskapande verksamhet i skärningen mellan dessa två områden, och ännu relativt få tidigare studier, finns det således ett intresse att undersöka hur dessa två områden kan integreras. Syftet med arbetet formuleras som en ansats att undersöka integreringen av hållbarhetsdata inom Business Intelligence (BI) för företag inom greentech, alltså företag vars mål är att nyttja teknik för att bidra till en mer hållbar framtid. Utifrån detta genereras sedan riktlinjer och insikter kring god design och implikationer för verksamheten. En tvärvetenskaplig ansats utnyttjas där vedertagen designteori, såsom Donald Normans designprinciper och utvecklingsramverket Action Design Research, kombineras med teori för informationssystem och Business Intelligence. I praktiken har detta inneburit en iterativ process där en prototyp av ett Business Intelligence-verktyg utvecklats för att visualisera hållbarhetsdata för ett greentech-företag. Verktyget har kontinuerligt utvärderats av representanter från olika funktioner i företaget för att undersöka vilka faktorer som är viktigast för hög användbarhet samt vilka effekter mer lättillgängliga hållbarhetsdata har på verksamheten. Undersökningen visar bland annat att det är av stor vikt att verktyget knyts nära övrig verksamhet, både designmässigt och verksamhetsmässigt, samt att en högt efterfrågad funktionalitet är att kunna segmentera och jämföra data på många olika sätt. Samtidigt finns flera aspekter som adderar komplexitet till frågeställningen, exempelvis en motsättning mellan organisationen och medarbetarna kring huruvida svenska eller engelska bör användas som språk i verktyget. Dessutom pekar också resultaten på att en avsaknad av lätt tillgängliga och korrekta data kan resultera i att beslut fattas baserat på intuition och erfarenhet, trots litteraturens avrådan. Någonting annat som även framkommit under testerna är trenden att allt fler företag behöver rapportera mer hållbarhetsinformation, och området därför är högaktuellt för vidare undersökningar.

This thesis investigates the relationship between value creation and complexity within Business Intelligence (BI) systems. The research questions posed are: "What makes a BI system vary in complexity?" and "In what ways can BI systems generate value for users, and how is this value affected by the systems’ complexity?" The study explores these dimensions of complexity and value using a qualitative approach, the study gathers data from multiple sources, including interviews with BI system users and experts, basic surveys, as well as an analysis of existing literature. The collected data suggest that financial analysis regarding what makes a BI system valuable is mostly irrelevant. What makes a BI system valuable is therefore not quantifiable. For individual users, the time savings compared to getting the same results without the system are what create high value. From a broader organizational perspective, the perceived value is based on whether the system makes the business processes more efficient and the decision-making of higher quality. The findings also suggest that the complexity of BI systems can significantly influence their value creation potential.  Furthermore, the study identifies that the perceived value of BI-systems increases alongside complexity to a certain point, after which the value instead could decrease. We argue that understanding and managing complexity is crucial for optimizing the value generated by BI systems. The findings of this research provide valuable insights for organizations seeking to develop or enhance their BI systems, by shedding light on the relationship between complexity and value creation.

Philosophiae Doctor - PhD / Business Intelligence refers to the use of Information Systems to enable raw data to be collated into information that can be reported, with the end goal of using this information to enhance the business decision-making process. Business Intelligence is enabled by making use of information that is complete, relevant, accurate, timely and accessible. There are currently a number of documented perspectives that can be used to gauge the value of Business Intelligence systems; however, from an overall business value perspective the most robust method would be to identify and analyse the most commonly identified factors that impact the value assigned to Business Intelligence Systems by a company, and the correlation of each of these factors to calculate the overall value. The importance of deriving a conceptual model, representing the major factors identified from literature and moderated by the quantitative research conducted, lies in its enabling companies and government bodies to assess the true value addition of Business Intelligence systems, and to understand the return on investment of these systems for organisations. In doing so, companies can justify or reject any further expenditure on Business Intelligence. The quantitative research for this thesis was conducted together with a project that was run between the University of the Western Cape and the Hochschule Neu-Ulm University of Applied Sciences in Germany. The research was conducted simultaneously across organisations in South Africa and Germany on the use of BI Systems and Corporate Performance Management. The respondents for the research were Chief Executive Officers, Chief Information Officers and Business Intelligence Managers in selected organisations. A Direct Oblimin-factor analysis was conducted on the online survey responses. The survey was conducted on a sample of approximately 1500 Business Intelligence specialists across South Africa and Germany; and 113 responses were gathered. The factor analysis reduced the key factors identified in the literature to a few major factors, namely: Information Quality, Management and Accessibility, Information Usage, and Knowledge-sharing Culture. Thereafter, a Structural-Equation-Modelling analysis was completed using the Partial-least-Squares method. The results indicate that there is a strong relationship between the factor-Information Quality, Management and Accessibility, and the Value of Business Intelligence. It was found that while there was no strong impact from Information Usage and Culture, there was a strong correlation between Information Usage and Culture and Information Quality, Management and Accessibility The research findings are significant for academic researchers, information technology experts, Business Intelligence specialists and Business Intelligence users. This study contributes to the body of knowledge by bringing together disparate factors that have been identified in academic journals; and assessing the relationship each has on the value of Business Intelligence, as well as the correlations that exist between these factors. From this, the final conceptual model was derived using factors that were identified and tested through the Factor Analysis and the PLS-SEM. The following conclusions can be drawn from the research: (1) The assurance of quality information in the form of complete, accurate, relevant and timeous information that is efficiently managed is the most paramount factor to an organisation deriving value from Business Intelligence systems; (2) information accessibility is key, in order to realise the value of Business Intelligence systems in organisations; and (3) Business Intelligence systems cannot add value to an organisation if a culture of information use and sharing is absent within that organisation. The derived model can be practically implemented as a checklist for organisations to assess Business Intelligence system investments as well as current implementations

Quantum systems with finite Hilbert space where position x and momentum p take values in Z(d) (integers modulo d) are considered. Symplectic tranformations S(2¿,Z(p)) in ¿-partite finite quantum systems are studied and constructed explicitly. Examples of applying such simple method is given for the case of bi-partite and tri-partite systems. The quantum correlations between the sub-systems after applying these transformations are discussed and quantified using various methods. An extended phase-space x¿p¿X¿P where X, P ¿ Z(d) are position increment and momentum increment, is introduced. In this phase space the extended Wigner and Weyl functions are defined and their marginal properties are studied. The fourth order interference in the extended phase space is studied and verified using the extended Wigner function. It is seen that for both pure and mixed states the fourth order interference can be obtained. / Ministry of Higher Education, Sultanate of Oman

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There is a requirement for English teachers in Sweden to adapt their teaching to align with the policy documents advocating to foster the students' continuous and lifelong learning. This study aims to address in what way the participating teachers work to create engaging learning environments and lessons that promote communication and cooperation. Furthermore, the study explores which methods the participating teachers use to differentiate instructions and make adaptations to teacher practices and materials to successfully reach each individual student. The data was gathered by conducting qualitative semi-structured interviews with four 7-9 English teachers. The interviews were focused on four main themes: (1) Adaptations for differentiated learning through multi-modality, (2) Adaptations for differentiated learning through the bi-lingual approach, (3) Adaptations for differentiated learning through cooperative learning and (4) Adaptations for differentiated learning through other practices. Based on the guidelines provided by The Swedish National Agency for Education, findings from previous research, and the data collected in this study, it becomes evident that teachers must adopt their teaching in various ways. The adaptation of teaching strategies and practices include ways to effectively engage all of their individual groups of students, as well as the utilization of visual aids, bi-lingual instructional practices, comprehensible input and output, and cooperative learning methods. The results show that these are important ways to differentiate instruction and enhance learning to support the students’ academic and cognitive growth. The presented teacher practices can aid teachers to use differentiated instruction in accordance with the needs of their individual groups of students, both in terms of classes and the individual students within those classes.