No description available.

Zugl.: Münster (Westfalen), Universiẗat, Diss., 2004.

Inom Business Intelligence har begreppet Self-Service Business Intelligence (Self-Service BI) vuxit fram. Self-Service BI omfattar verktyg vilka möjliggör för slutanvändare att göra analyser och skapa rapporter utan teknisk support. Ett av dessa verktyg är Microsoft PowerPivot.På Transportstyrelsens Järnvägsavdelning finns behov av ett Self-Service BI-verktyg. Vi fick i uppdrag av Sogeti att undersöka om PowerPivot var ett lämpligt verktyg för Transportstyrelsen. Målet med uppsatsen har varit att testa vilka tekniska möjligheter och begränsningar PowerPivot har samt huruvida PowerPivot är användbart för Transportstyrelsen.För att få en djupare förståelse för Self-Service BI har vi kartlagt vilka möjligheter och begränsningar med Self-Service BI-verktyg som finns beskrivna i litteraturen. Vi har sedan jämfört dessa med våra testresultat vilket har varit syftet med uppsatsen.Resultatet av testerna har visat att Transportstyrelsens Järnvägsavdelning initialt behöver teknisk support för att använda PowerPivot. Testerna har även visat att vissa av Transportstyrelsens krav inte kan uppfyllas. Detta minskar användbarheten för Transportstyrelsen.Vidare har vi kommit fram till att Self-Service BI inte alltid är enkelt att använda för slutanvändare utan teknisk support. Resultatet visar även att det krävs en BI-infrastruktur för att enkelt skapa rapporter med god kvalitet och högsta möjliga korrekthet.

Fachhochschule Gießen-Friedberg, Diplomarbeit--Gießen, 2007.

With today's rapidly changing business environment, more and more businesses are using competitive intelligence to improve planning efforts, identify threats and opportunities and help avoid unpleasant surprises. However, to be effective, this intelligence must be gathered and communicated between managers. Two research questions will address these issues: (1) can a representation of competitive knowledge be developed that reflects managerial thought and (2) will a graphical computer tool based on this representation elicit a more complete representation of competitive intelligence knowledge in a more efficient manner relative to traditional methods? Various studies have shown managerial thought to be represented in several ways, e.g., conceptual groupings, hierarchically, and causally. However, by proposing that managers represent information about competitors in a story structure and integrating this proposal with the literature from competitive intelligence and strategic planning, a more complete conceptual model results. To validate the proposed conceptual model, an archival case study of three competitors in the computer workstation market was conducted. Following that, interviews were conducted with six MBA students with experience in competitive intelligence and with six managers. The transcripts from these interviews have been analyzed and the conceptual model has been modified based on input from this content analysis. A prototype was developed using the ConceptBase platform, an X-windows tool that provides both graphical and textual access to concepts and their relationships. The prototype will allow managers to create a graphical representation of their competitive knowledge. This representation will allow managers to locate gaps in their knowledge and to communicate their information to others. The prototype was validated by two different groups of MBA students by asking them to represent a given competitive situation. One group used pencil and paper while the second group used the prototype. Both the number of uncategorized concepts and the number of relationships differed significantly. This indicates that a more complete representation was created using the prototype. The two main contributions of this research are: (1) a model of competitive intelligence knowledge based on managerial cognition, and (2) a prototype that will facilitate the elicitation of competitive intelligence knowledge in a graphical and understandable manner.

Presentación realizada en el marco de las IV Jornadas de usuarios Ex Libris. Arequipa, Perú. 02-03 de Julio 2015 / said.castro@upc.edu.pe

Made available in DSpace on 2014-06-12T17:40:03Z (GMT). No. of bitstreams: 2 arquivo7002_1.pdf: 1571231 bytes, checksum: cebc67c576395c8690fff85d3b2170bb (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2004 / Aplicativos computacionais utilizam diferentes estruturas de programação, sintaxe, e semântica para modelar seus metadados, gerando grandes incompatibilidades quanto há a necessidade de interação com outras aplicações. O OMG vem trabalhando no estabelecimento do CWM (Common Warehouse Metamodel) como padrão para a integração de metadados nos domínios de data warehouse e business intelligence. Nesta dissertação primeiramente foram abordados os aspectos gerais dos metadados e de suas arquiteturas de integração, para em seguida se pesquisar a aplicação dos metamodelos que compõem o CWM e suas tecnologias de fundamentação (UML, MOF, XMI) Desenvolveu-se a modelagem de um aspecto referente ao orçamento público existente em todas as instancias governamentais utilizando-se alguns dos metamodelos CWM, como forma de se demonstrar a facilidade na troca de metadados entre os diversos recursos de dados

No description available.

Due to the fast development of new technologies, the Business Intelligence market is changing rapidly, forcing vendors to adapt their offerings to the customers’ needs. As the amount of data available to companies has been substantially increasing in the past years, the need of suitable software tools that perform the right analyses became essential, even in the small and medium sized business' environment. The previous literature,focused on big firms and traditional implementation of Business Intelligence solutions, highlighted the importance of understanding the key factors in successful projects. In the past few years, a new delivery model for Business Intelligence software is taking place: the cloud computing. To date, key factors for adopting cloud Business Intelligence in small and medium sized enterprises (SMEs) have not been systematically investigated. Existing studies have rarely considered these arguments and we lack of a proven framework. This paper is aimed to fill this gap and the structure of the article is subordinated to this objective. Firstly, the thesis offers an overview of the subject and the terminology used in it with the purpose of facilitating the understanding of a rather complex argument. Therefore, it starts with a short historical overview of the Business Intelligence sector, it defines the term Business Intelligence, and it explains both the characteristics of the Business Intelligence systems (cloud vs on-premise) and the importance of having a business intelligence solution for SME. Subsequently, the theoretical framework of this study is defined, combining the prior theories and empirical data collected through the interviews with four Business Intelligence vendors and customers. Initially, the existing Critical Success Factors (CSFs) of IT and BI projects proposed by different authors in the literature are reviewed. Afterwards, the evaluation criteria for the cloud software are taken into consideration. By integrating insights drawn from these studies, as well as adding new factors coming from the interviews, a framework has been created and utilized as a basis for the further questionnaire development. The choice of pursuing both the quantitative and qualitative approaches is aimed at improving the study’s reliability. Empirical data are mainly primary data, collected during a survey and four interviews, supported by secondary data such as general companies' reports, market and trends analysis from trustworthy sources. Based on the findings, the author of this thesis has ranked the key aspects of a cloud BI adoption in SMEs. It is revealed the most important key adoption factors that SMEs evaluate when purchasing a cloud BI solution are the level of software functionalities, the ubiquitous access to data, the responsive answers to customer support requests, the ability to handle big amount of data and the implementation cost. Regarding the managerial implications, the study’s practical relevance consists in offering to BI suppliers' managers, executives and decision-makers interesting areas of discussion for improving the knowledge of SMEs' needs. Moreover, the results of this investigation can be used by Business Intelligence newcomers as a guidance for evaluating solutions available in the market.

The area of Business Intelligence (BI) is both broad and multifaceted and is becoming an increasingly pervasive tool utilized within organizations allowing them to gain greater insight into their business operations as well as well as the way in which their customers interact with them. By enabling businesses to perform powerful, effective analytics and reporting, BI tools allow them to maximize use of their data and facilitate better planning, forecasting and the ability to have a more targeted and efficient value chain. Usage of BI tools allow organizations to not only achieve but leverage their competitive advantage. SMEs are no different in their pursuit for competitive advantage and market share but often is the case that they lack the resources in order to make the substantial investments into the software and infrastructure required to host a solution on-premise. The Software-as-a-Service (SaaS) model of allowing users to have access to powerful tools and services without having to purchase the solutions or the infrastructure needed to host it on-premise allows SMEs an ideal opportunity to perform many or all of the functionalities that on-premise BI provides. SaaS BI is a relatively new concept only a few years old, but improvements in functionality and features, reliability of service levels and lower costs are allowing it to gain traction and it is projected to increase its momentum in the next few years. The aim of this paper is to investigate the factors that lead to adoption/non-adoption, assigned importance and perceived business value of SaaS BI within SMEs. These issues will be addressed through identification of the key decision criteria that influence SMEs to adopt SaaS BI solutions over an on-premise solution and vice versa. Greater insight into the decision making process, usage and value will be investigated with the cooperation of two vendors within the BI field. A two pronged approach targeting both SaaS and on-premise BI vendors and the users is adopted in order to find out the perspective on either end and whether or not they are incongruent. Semi-structured interviews were targeted at both an on-premise vendor and a SaaS vendor and their customers. A questionnaire was deployed to clients of both these vendors. Analysis was then conducted on the findings using an integrated selection model encompassing BI and SaaS theories and concepts outlined in the paper.