Implementering av BI inom offentlig sektor är något som växer och blir vanligare och vanligare. För organisationer inom privata sektorn finns det tydliga och välbeprövade kritiska framgångsfaktorer att följa för att lyckas med implementationen. För den offentliga sektorn är detta inte lika tydligt och finns lite forskning. Denna studie har undersökt kritiska framgångsfaktorer för den offentliga sektorn vid BI implementation. Studien har utgått ifrån ett tidigare framtaget ramverk anpassat för den privata sektorn för att sedan urskilja med hjälp av erfarna personer inom området vilka kritiska framgångsfaktorer som finns för den offentliga sektorn. Studien har resulterat i ett vidareutvecklat ramverk anpassat för den offentliga sektorn. Studiens resultat framställer en tydlig skiftning från det tidigare ramverkets affärsfokus till ett mer verksamhetsfokus för den offentliga sektorn. Det vidareutvecklade ramverket framhäver även att det måste finnas en BI-mognad inom den offentliga verksamheten som inte var en kritisk framgångsfaktor inom det tidigare ramverket.

Information Systems (IS) is the use of Information Technology (IT). Business Intelligence (BI) is a specific type of IS. A BI system is an information system that uses tools to produce and deliver information. BI has become very important in the recent era as the organizational environments are getting more complex and changing faster than ever before. Research on BI uses in academia has been somewhat limited so far. Most decisions in a university are made based on large amounts of data from internal and external sources. So, a BI tool is necessary there in operational and strategic decision making, and also to compete well in the global environment which is very important for an international university like Uppsala. We made a case study on the large BI tool at Uppsala University. The tool has been used for more than ten years with around five hundred regular users currently. The system is called GLIS (in Swedish: Generellt Lednings Informations System) for Generalized Management Information System. It would be very interesting to investigate how the adoption of this BI system may influence the decision making process in Uppsala University, and thus it becomes the main purpose of this thesis. An inductive approach using a qualitative method was used in this thesis. The data collection was carried out by interviewing seven experts at Uppsala University and from some documents provided by them. Techniques from the grounded theory approach were applied for analyzing data. Our analysis shows positive effects of GLIS in Uppsala University with big improvements in decision making. The thesis draws a conclusion that the BI tool does affect the decision making process in UU as decision making activities take less time, provide better quality decisions, and are much easier using the tool. The thesis also suggests some possible improvements of GLIS for a better functionality and more user involvement. For IS practitioners, the thesis shows the power of IS tool in decision making and university management. For the IS research community, the thesis contributes with the extension of existing theory on BI uses in academia.

With mobile solutions becoming more requested in the IT world, Business Intelligence is no different. This thesis examines and tests the mobile solutions for Microsoft BI, QlikView and SAP Business Objects to see if it can be used by the Sandvik Group. The tests have consisted of creating standard simple reports for the different platforms, evaluate them and then compare their functions and looks on iPad and computers. During this work it has been stated that all platforms supports mobility quite well and the recommendation is to start using it as soon as possible.

Studien har handlat om att ta fram riktlinjer för hur extrahering, transformering och inladdning (ETL) av kreditbedömningsinformation bör göras när det kommer till att införa ett Data Warehouse (DW). Ett kvalitativt angreppssätt har använts med både en fallstudie och en intervjustudie, där fallstudien genomfördes med Asitis AB som är en systemleverantör förfinans- och reskontrafinansiering (factoring) för att undersöka potentiella affärsmöjligheter med ett DW med kreditbedömningsinformation. Intervjustudien användes för att samla in värdefull information från individer inom alla berörda problemområden, och användes sedan i fallstudien. Resultatet var både framgångsfaktorer och fallgropar för ETL-processen med kreditbedömningsinformation som kan fungera som stöd för organisationer med detta behov. Det har visat sig att ETL-processen för kreditbedömningsinformation utgör ett område med stor potential för affärsmöjligheter, där det krävs hög kompetens, domänkunskap, proaktivitet och juridisk kunskap vid genomförande av ETL-processen.

Det blir allt vanligare att företag väljer att använda mobila applikationer för att underlätta beslutstödshanteringen utanför kontoret. Dessa applikationer är så kallade mobilt business intelligence lösningar  som är starka verktyg för att kunna fatta beslut oavsett vart anställda befinner sig. I och med att mobilt business intelligence (MBI) börjar bli allt vanligare bland företag idag så är det väldigt användbart att känna till faktorer som gör det lättare att nå framgång med MBI. Idag finns det väldigt lite forskning kring framgångsfaktorer för att lyckas med MBI lösningar. Därför har denna studie behandlat ett par framgångsfaktorer inom området system innehåll och kvalitet för att ta reda på hur kritiska vissa befintliga faktorer egentligen är för att lyckas med MBI lösningar i dagens företag. Resultatet visade sig att vissa av framgångsfaktorerna så som stöd för interaktiva konferenser var mindre betydelsefulla jämförelse med andra framgångsfaktorer för att nå framgång med MBI. Studien tar även fram problem och svårigheter som nätverksproblem, extra arbete prestanda försämring med flera som kan uppstå med att uppnå kritiska framgångsfaktorer.

Business intelligence (BI) is an umbrella term used to describe the applications,infrastructure and tools, and best practices which organizations canuse to analyze information in order to improve and optimize decisions andorganizational performance. In the later years a new trend has emerged inthe area of BI namely, Self-Service Business Intelligence. The purpose ofSelf-Service BI is to empower the users by allowing users to create reportsand analyze data without support of the IT department. This thesis have tested and evaluated Microsoft's new Self-Service BI toolsuite, Power BI, through a case study in a large organization. The mainpurpose was not only to conclude if it is possible to implement a completeSelf-Service BI solution in a large organization, but also examine which partsof the Business Intelligence architecture are most suitable for implementingPower BI. The result have shown that Power BI and Self-Service BI tools can't meetthe back-end requirements of a large organization and therefore it is not asuitable or functional solution. However, the front-end applications and bestpractises of Power BI and Self-Service BI are suitable for a large business.They support the users needs and empowers the users create better andmore powerful analysis.

Data have become number one assets of today's business world. Thus, its exploitation and analysis attracted the attention of people from different fields and having different technical backgrounds. Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. However, designing and optimizing such data flows, to satisfy both users' information needs and agreed quality standards, have been known as a burdensome task, typically left to the manual efforts of a BI system designer. These tasks have become even more challenging for next generation BI systems, where data flows typically need to combine data from in-house transactional storages, and data coming from external sources, in a variety of formats (e.g. social media, governmental data, news feeds). Moreover, for making an impact to business outcomes, data flows are expected to answer unanticipated analytical needs of a broader set of business users' and deliver valuable information in near real-time (i.e. at the right time). These challenges largely indicate a need for boosting the automation of the design and optimization of data-intensive flows. This PhD thesis aims at providing automatable means for managing the lifecycle of data-intensive flows. The study primarily analyzes the remaining challenges to be solved in the field of data-intensive flows, by performing a survey of current literature, and envisioning an architecture for managing the lifecycle of data-intensive flows. Following the proposed architecture, we further focus on providing automatic techniques for covering different phases of the data-intensive flows' lifecycle. In particular, the thesis first proposes an approach (CoAl) for incremental design of data-intensive flows, by means of multi-flow consolidation. CoAl not only facilitates the maintenance of data flow designs in front of changing information needs, but also supports the multi-flow optimization of data-intensive flows, by maximizing their reuse. Next, in the data warehousing (DW) context, we propose a complementary method (ORE) for incremental design of the target DW schema, along with systematically tracing the evolution metadata, which can further facilitate the design of back-end data-intensive flows (i.e. ETL processes). The thesis then studies the problem of implementing data-intensive flows into deployable formats of different execution engines, and proposes the BabbleFlow system for translating logical data-intensive flows into executable formats, spanning single or multiple execution engines. Lastly, the thesis focuses on managing the execution of data-intensive flows on distributed data processing platforms, and to this end, proposes an algorithm (H-WorD) for supporting the scheduling of data-intensive flows by workload-driven redistribution of data in computing clusters. The overall outcome of this thesis an end-to-end platform for managing the lifecycle of data-intensive flows, called Quarry. The techniques proposed in this thesis, plugged to the Quarry platform, largely facilitate the manual efforts, and assist users of different technical skills in their analytical tasks. Finally, the results of this thesis largely contribute to the field of data-intensive flows in today's BI systems, and advocate for further attention by both academia and industry to the problems of design and optimization of data-intensive flows. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Abstract : Manufacturing companies in developed countries face a digital transformation that is meant to improve their productivity, but also produces a large volume of data. This data will go to waste if it is not valorized by using it to gain actionable insights, for example with business intelligence and analytics. This master’s thesis presents a systematic literature review and a multiple case-study on the subject of Business Intelligence in manufacturing companies. The first article, “Business Intelligence in Industry 4.0: Research opportunities”, present a literature review. Results show a lack of studies on the impacts of business intelligence activities on manufacturing small and medium enterprises. The strategic impacts should be studied, since they are often neglected in favor of the operational impacts such as quality improvement and operating costs reductions. The second article, “Business intelligence value creation: A multiple case study in manufacturing SMEs”, presents an exploration of the factors influencing strategic and operational business values of business intelligence. Results show the limit of the traditional models based on the Resource-Based View of the firm, which overlooks organizational factors that might be more important in smaller organizations. Contingency factors, such as organisational learning, leadership style, and the role of the owner, should be included when studying small and medium enterprises, as in these smaller organizations the lack of resources and the simpler structure affect business value of business intelligence and analytics systems differently than in larger firms. There is an interesting potential for the model suggested in this master’s thesis to understand the factors linked to business value creation in smaller organization, which should be empirically tested with a larger and more diverse sample in a future study. / Ce mémoire présente les travaux réalisés dans le cadre de ma maîtrise en Stratégie de l’intelligence d’affaires, de l’École de Gestion de l’Université de Sherbrooke. Il consiste en deux articles. Le premier est une revue de littérature systématique ayant été soumise et acceptées à la 51e édition de Hawaii International Conference on System Sciences, qui a eu lieu du 3 au 6 janvier 2018. Il est présenté intégralement au chapitre deux. Le second article, présenté dans sa version longue au chapitre trois, a été soumis à la 7e édition de International Conference on Information Systems, Logistics and Supply Chain qui aura lieu du 8 au 10 juillet 2018. Les notices d’acceptation seront envoyées après la date de dépôt de ce mémoire. Toutes les preuves de soumissions sont présentées dans les annexes de ce mémoire. Les articles ont tous été rédigé par moi, Fanny-Ève Bordeleau, qui a également réalisé toutes les prises de données et les analyses, assistée de mes co-directeurs, les professeurs Elaine Mosconi et Luis Antonio De Santa-Eulalia.

Das Ziel dieser Arbeit ist es zu zeigen, wie gut webbasierte Daten für Positionierungsanalysen von Unternehmen geeignet sind. Dazu werden die Ergebnisse einer quantitativen Marktstudie mittels Fragebogen mit den Resultaten einer Datenerhebung aus dem Web mit statistischen Verfahren und mit einem eigenen Gütekriterium verglichen. Durch die Anwendung von multivariaten Analyseverfahren wird gezeigt, inwieweit die webbasierten Daten zur Beschreibung von Marktsituationen geeignet sind. Die Weberhebung ist in Form eines Softwaremoduls realisiert, das auch praktisch in Unternehmen zum Einsatz kommen kann. Somit soll den Marketing-Managern in Unternehmen die Moglichkeit gegeben werden, die in dieser Arbeit entwickelten Methoden direkt anzuwenden. Deshalb wurde darauf geachtet, dass einerseits nur frei verfügbare Quellen verwendet werden, andererseits soll die Bedienung der Software ohne spezielle informationstechnologische Kenntnisse möglich sein.

The social media development has made it harder for companies to understand their consumers. Companies are using Facebook and Instagram for their digital marketing strategies in greater extent today, but does all of them know what their campaigns on Facebook result in? Do they have knowledge about which people that really are interested in the published content on Instagram? This study aims to improve companies understanding about Business Intelligence and digital marketing. By examining how Business Intelligence is used among Swedish companies on social media platforms, like Facebook and Instagram, can the research question ”How can Swedish companies use Business Intelligence while conducting social media marketing?” be answered. Strategies using Business Intelligence on social media are showing through a qualitative method using individual interviews with three Swedish companies. The interviewees are at the forefront of the use of Business Intelligence in their digital marketing. The empirical chapter shows, among other things, that Business Intelligence gives companies more information about their consumers on Facebook and Instagram, which they can use to create customized content regarding their consumers interests. Additionally the result indicate that Business Intelligence is not as hard to use as companies think. The tools that are considered best are still free and there already exist a lot of data about companies consumers in organizations. When companies are understanding the importance of using the collected data from marketing campaigns it is easier to save money through analyzes and conduct strategies based on the information. This study shows that leaders from the younger generation have more knowledge about Business Intelligence which will affect the digital marketing strategies in the future. The use of Business Intelligence in social media marketing enables to create the content that the target audience are requesting. By creating content based on the audience interest and past engagement in marketing campaigns, companies messages can easily be understood and reach the right people. Using Business Intelligence in conjunction with social media can lead to reduced costs as companies will focus on the engaging content instead of using unnecessary money and resources to create non engaging content.