Business intelligence is an effort to better understanding of company processes and business consequences in which company occur. The main goal of this thesis is to characterize the principles and possibilities of implementation and application Business intelligence in small or medium enterprise. This goal should be achieved by description of general needs which small or medium enterprise, looking forward to use business intelligence, has. This includes evaluation and universal description of information technologies in small and medium enterprises, as well as what data are used for managerial decisions and how are they made. In order to implement BI into the small or medium enterprise, it is necessary to imply how the Business intelligence work and on what principles. The application part of this thesis describes real procedures in preparation of BI implementation, impact on company and evaluation of the meaningfulness of this solution.

Made available in DSpace on 2016-06-02T19:51:39Z (GMT). No. of bitstreams: 1 2385.pdf: 3560559 bytes, checksum: 71e6c5c7aca71d06463f1bc0bc063005 (MD5) Previous issue date: 2009-02-27 / In the past decades companies around the world have implemented their concepts of Lean Manufacture (LM) with their main focus on business. Together with LM s implementation comes the need of continuous improvement as several sources and historical data volume originate from its processing. Whenever those historical data are, for any reason, discarded without generating indicators the oportunity of transforming data into strategic information is missed. Such situation brings about the need of an adequate performance measurement system of LM. Having this constant monitoring need of LM s performance in mind as a strategic mean for a company to achieve competitivity in the market, this paper aims to develop through Information Technology (IT) and the tools of Business Intelligence (BI) a proposal of managing performance indicators of LM present in shoe production, as an alternative to improve decision making. In order to develop this research, an overview of the literature of LM, BI, Information Systems (IS), performance indicators and shoe manufacturing from the basic concept of LM is offered that, on the other hand, has to do with cost reduction and total cut of waste. This study leads to the seven waste groups of LM, which, together with other published works, can guide and focus so as to reach indicators. By setting indicators and pointing strategy, and also collecting data, the next step is modelling and developing data load in dimentional format prepared to use BI s tools as On-line Analytical Processing (OLAP). Finally, the application is tested in a shoe industry with the load of waste indicator for over production. The final result of the research is a series of analyses of waste information for over production as well as the contribution of the proposed method in terms of easiness, flexibility and practical availability in companies. / Nas últimas décadas, empresas do mundo inteiro têm implementado os conceitos da Manufatura Enxuta (ME) com objetivo estratégico para os negócios. Conforme a manufatura enxuta é implementada, surge também a necessidade de melhoria contínua, e conseqüentemente aparecem várias fontes e volume de dados histórico advindos do seu processamento. Quando esses dados históricos por qualquer motivo são descartados sem gerar indicadores, é desperdiçada a oportunidade de transformar os dados em informação estratégica. Esta situação expõe a necessidade de um adequado sistema de medição de desempenho da manufatura enxuta. Entendendo esta necessidade de monitoramento constante do desempenho da Manufatura Enxuta (ME) como um fator estratégico para as empresas obterem competitividade no mercado; este trabalho busca desenvolver através da Tecnologia da Informação (TI) e das ferramentas de Business Intelligence (BI) uma proposta de gerenciamento de indicadores de desempenho da Manufatura Enxuta (ME) presentes na produção de calçados, como uma alternativa para melhorar a tomada de decisão. Para o desenvolvimento do trabalho foi feita uma revisão da literatura de Manufatura Enxuta (ME), Sistemas de Informação (SI), Business Intelligence (BI), indicadores de desempenho e manufatura de calçados com base no conceito da Manufatura Enxuta (ME), que é a redução de custo pela total eliminação de desperdícios. Isto leva aos sete grupos de desperdício da Manufatura Enxuta (ME), que por sua vez, em conjunto com outros trabalhos publicados, servem de guia e foco para encontrar os indicadores. Com a definição dos indicadores e a estratégia de apontamento e carga dos dados, o próximo passo é uma modelagem e desenvolvimento da carga dos dados em formato dimensional, preparado para utilização de ferramentas de Business Intelligence (BI) como On-line Analytical Processing (OLAP). Por último a aplicação é testada numa indústria de calçados com a carga do indicador de perda por super produção. O resultado final do trabalho é uma série de análises das informações de perda por superprodução, assim como a contribuição do método proposto em termos de facilidade, flexibilidade e viabilidade para uso prático nas empresas.

ABSTRACT Date:  2021-06-03 Level:  Bachelor Thesis in Business Administration, 15 cr Institution: School of Business, Society and Engineering, Mälardalen University Authors: Aryan Singh   Omar Eyad  Shaheen Mohammad  Title:  How Market Intelligence Helps With Pricing Tutor:  Ali Farashah Keywords: Digitalization, Business Intelligence (BI), Market Intelligence (MI), Competitive Intelligence (CI), Pricing, Decision Making, Dynamic Pricing Model, Price Authority Research Question: How does MI help in pricing decisions of the European market in Systemair Purpose: The purpose of this research is to investigate if Market Intelligence (MI) has any effect on pricing decisions within the European market in Systemair Group. Since the field of MI in pricing decisions is explorative, this study will conduct thorough interviews with the goal of getting a deep understanding of how MI can help with pricing decisions. This study also aims to contribute to the research in this subject. Method: This study has been conducted in a qualitative manner on the case company Systemair Group. Primary data was collected through academic articles found via the library of Mälardalen University and scientific databases. The research was based on 5 semi-structured interviews conducted online with employees of Systemair. Conclusion: MI plays an important role in pricing. It gathers real time market data that is objective to feelings from the sales team or other employees. Factory capacity will be optimized with the evolution of MI, profit margin will be set higher than before and so this will result in a push in the overall price level of Systemair products. Value-Based Selling points and Resources are an integral part of the dynamic pricing model, specifically in Strategic Input and Data Input respectively.

Denna studie undersöker hur artificiell intelligens (AI) kan optimera beslutsstödet inom verksamhetsstyrning genom analys av ostrukturerad data. Genom att granska begrepp som verksamhetsstyrning, Business Intelligence (BI), AI och maskininlärning (ML), belyser studien hur dessa teknologier kan förbättra organisationers beslutsprocesser. Verksamhetsstyrning syftar till att samordna och optimera organisationens delar för att nå gemensamma mål. AI (NLP, ML) samt särskilt genom BI spelar en avgörande roll genom att förbättra effektivitet och kvalitet. BI samlar och analyserar affärsinformation, medan ML möjliggör automatisk lärande från data. Studiens problemområde identifierar utmaningen med att hantera stora mängder ostrukturerad data. Trots AI:s potential att förbättra beslutsfattandet har dess fulla potential ännu inte realiserats. Genom att undersöka effektiv användning av AI för ostrukturerad data, bidrar studien till en bättre förståelse av hur AI kan förbättra beslutsstödet.Den kvalitativa ansatsen använde semistrukturerade intervjuer med IT-experter för att samla insikter om AI:s användning i beslutsfattande. Respondenterna beskrev hur AI analyserar data, förutsäger trender, optimerar processer och personaliserar kundupplevelser. AI automatiserar också tidskrävande uppgifter, vilket ökar effektiviteten och frigör tid för strategiskt arbete. Det visar att AI kan förbättra datakvalitet, automatisera processer och ge djupare insikter i kundbeteenden och marknadstrender. AI:s förmåga att hantera ostrukturerad data möjliggör identifiering av trender och mönster som annars skulle vara svåra att upptäcka. Utmaningar med AI-implementering inkluderar systemintegrering och behovet av teknisk expertis. Sammanfattningsvis visar studien att AI har stor potential att optimera beslutsstödet inom verksamhetsstyrning genom analys av ostrukturerad data.

平衡計分卡( Balanced Scorecard, BSC)是一項可以協助描述、並推動組織策略付諸實行的利器，關於描述組織之價值創造的四個構面模式，可以當成高階管理團隊彼此間討論企業發展方向與策略議題優先性的共同語言。至於有關策略性衡量指標，除了是四大構面的績效指標之外，也應被視為BSC內四個構面具有因果關係連結的目標、項目；Robert S. Kaplan和David P. Norton共同創造出一個關於此連結的通用表達方式，用來協助高階主管進行討論，並稱之為策略地圖。他們同時也證明了BSC所寄託的一個基本原則，那就是「如果您能夠衡量，就可以管理」 從實務經驗中大多數人都會認為管理資訊系統不僅協助企業管理工作，也是產出各種衡量數據的利器，因此本研」究希望透過分析已導入過BSC之個案公司，探討該公司由策略地圖所引導出來的各項策略性衡量指標的資訊需求，是否能夠在其管理資訊系統中獲得滿足？管理資訊系統的建置是否應該優先支援公司策略性目標？實際上探訪各行業導入BSC之狀況，發現普遍存在著「數據落差」。 本研究旨在建構一套能夠彌補「數據落差的資訊需求規劃模式，利用商業智慧(BI)工具擷取ERP、CRM、SCM、Workflow、KM、e-Learning等管理資訊系統之有效數據，進行資訊加工後，提供給BSC資訊系統，在數位儀表板上顯示，以協助隨時管控策略性衡量指標之達成狀況。本研究也將BSC導入程序及資訊系統整合作業加以制式化，整理成BSC導入專案進度表，供其它有意導入BSC之企業參考，本論文最後延伸說明BSC在協助組織變革管理、協助智慧資本之衡量、及審視資訊資本齊備程度等方面，都很有助益。 / Balanced Scorecard (BSC) is a powerful tool for describing and implementing an organization’s strategy. The four-perspective model of describing a value-creating organization can be regards as a language for executive teams to discuss the direction and priority of their strategic agenda. In terms of strategy measures, they do not only represent as the key performance indicators (KPIs) of four independent perspectives, but also regard as the cause-effect linkage of goals and items among the four perspectives of BSC. Robert S. Kaplan and David P. Norton created the expression model of the cause-effect linkage to assist the discussion process of executive teams. It is so called a strategy map. They both also demonstrated a fundamental principle underling the BSC; i.e. “If you can measure, you can manage it.” From an empirical perspective, people believe that management information systems (MISs) can help the efficiency and effectiveness of business administration as well as be the powerful tool of generating data for various performance measures. Therefore, by analyzing a case of a BSC roll-out enterprise, this research would like to address whether the data requirements of strategic measures generating from strategy maps are fulfilled by the data output from the MISs or not. Is it a necessity to support the strategic goals of an enterprise first in case of building MISs for an enterprise? After studying the status of roll-out BSC enterprises in different industries, it shows that there is a “KPI-data accuracy” issue between actual KPIs needed and the data resources from. The purpose of this research is to build a data requirement planning model to find out the “accurate data” by using a business intelligence (BI) tool to access the effective information from ERP, CRM, SCM, Workflow, KM, e-Learning; etc., and then to manipulate those data in order to output the BSC indicators for executive teams for monitoring the status achieved of BSC from the dashboard anytime. Moreover, the study also standardizes the BSC roll-out processes and the integration processes of MISs by summarizing into time tables of project management which can be regarded as a reference kit for enterprises intending to implement BSC in the future. Finally, the study also demonstrates the benefits of BSC in assisting change management of an organization, in evaluating the intellectual capital, and in measuring information capital readiness of an enterprise, etc.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Despite the potential benefits of a DW, data quality issues prevent users from realizing the benefits of a BI environment and Data Analytics. Problems related to data quality can arise in any stage of the ETL (Extract, Transform and Load) process, especially in the loading phase. This thesis presents an approach to automate the selection and execution of previously identified test cases for loading procedures in BI environments and Data Analytics based on DW. To verify and validate the approach, a unit test framework was developed. The overall goal is achieve data quality improvement. The specific aim is reduce test effort and, consequently, promote test activities in DW process. The experimental evaluation was performed by two controlled experiments in the industry. The first one was carried out to investigate the adequacy of the proposed method for DW procedures development. The Second one was carried out to investigate the adequacy of the proposed method against a generic framework for DW procedures development. Both results showed that our approach clearly reduces test effort and coding errors during the testing phase in decision support environments. / A qualidade de um produto de software está diretamente relacionada com os testes empregados durante o seu desenvolvimento. Embora os processos de testes para softwares aplicativos e sistemas transacionais já apresentem um alto grau de maturidade, estes devem ser investigados para os processos de testes em um ambiente de Business Intelligence (BI) e Data Analytics. As diferenças deste ambiente em relação aos demais tipos de sistemas fazem com que os processos e ferramentas de testes existentes precisem ser ajustados a uma nova realidade. Neste contexto, grande parte das aplicações de Business Intelligence (BI) efetivas depende de um Data Warehouse (DW), um repositório histórico de dados projetado para dar suporte a processos de tomada de decisão. São as cargas de dados para o DW que merecem atenção especial relativa aos testes, por englobar procedimentos críticos em relação à qualidade. Este trabalho propõe uma abordagem de testes, baseada em um framework de testes unitários, para procedimentos de carga em um ambiente de BI e Data Analytics. O framework proposto, com base em metadados sobre as rotinas de carga, realiza a execução automática de casos de testes, por meio da geração de estados iniciais e a análise dos estados finais, bem como seleciona os casos de testes a serem aplicados. O objetivo é melhorar a qualidade dos procedimentos de carga de dados e reduzir o tempo empregado no processo de testes. A avaliação experimental foi realizada através de dois experimentos controlados executados na indústria. O primeiro avaliou a utilização de casos de testes para as rotinas de carga, comparando a efetividade do framework com uma abordagem manual. O segundo experimento efetuou uma comparação com um framework genérico e similar do mercado. Os resultados indicaram que o framework pode contribuir para o aumento da produtividade e redução dos erros de codificação durante a fase de testes em ambientes de suporte à decisão.

Business Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Without an effective Data Warehouse, organizations cannot extract the data required for information analysis in time to enable more effective strategic, tactical, and operational insights. This thesis presents an approach and a Rapid Application Development (RAD) tool to increase efficiency and effectiveness of ETL (Extract, Transform and Load) programs creation and maintenance. Experiment evaluation of the approach is carried out in two controlled experiments that carefully evaluated the efficiency and effectiveness of the tool in an industrial setting. The results indicate that our approach can indeed be used as method aimed at improving creation and maintenance of ETL processes. / Grande parte das aplicações de Business Intelligence (BI) efetivas depende de um Data Warehouse (DW), um repositório histórico de dados projetado para dar suporte a processos de tomada de decisão. Sem um DW eficiente, as organizações tendem a não extrair, em um tempo aceitável, os dados que viabilizam ações estratégicas, táticas e operacionais mais eficazes. Muitos ambientes de BI possuem um processo de Engenharia de Software particular, baseado em dados, para desenvolver programas de Extração, Transformação e Carga (ETL) de dados para o DW. Este trabalho propõe o desenvolvimento e experimentação de uma abordagem de Desenvolvimento Rápido de Aplicações (RAD) para aumentar a eficácia e a eficiência da manutenção de procedimentos de carga SQL, utilizados em processos ETL, avaliando a relação existente entre a sua utilização e a qualidade dos dados que são movidos, gerados e atualizados durante o processo de povoamento de um Data Warehouse. Este é um ambiente ímpar que necessita de maior integração e interdisciplinaridade entre as áreas de Engenharia de Software (ES) e Banco de Dados. Foi feita uma avaliação da criação e manutenção automática de procedimentos em extensões da SQL, perfazendo dois experimentos controlados feitos na indústria, para analisar a efetividade de uma ferramenta que encapsula e automatiza parte da abordagem. Os resultados indicaram que a nossa abordagem pode ser usada como método para acelerar e melhorar o desenvolvimento e manutenção de processos ETL.

This thesis deals with the areas of enterprise data quality, data integrity and data consolidation from the perspective of Business Intelligence (BI), which is currently experiencing significant growth. The aim of this thesis is to provide a comprehensive view of the data quality in terms of BI, to analyze problems in the area of data quality control and to propose options to address them. Moreover, the thesis aims to analyze and assess the features of specialized software tools for data quality. Last but not least aim of this thesis is to identify the critical success factors in the field of data quality in CRM and BI projects. The thesis is divided into two parts. The first (theoretical) part deals with data quality, data integrity and consolidation of data in relation to BI trying to identify key issues, which are related to these areas. The second (practical) part of the thesis deals at first with the features of software tools for data quality and offers their fundamental summary as well as the tools breakdown. This part also provides basic comparison of the few selected software products specialized at the corporate data quality assurance. The practical part hereafter describes addressing the data quality within the specific BI/CRM project conducted by Clever Decision Ltd. This thesis is intended primarily for BI and data quality experts, as well as the others who are interested in these disciplines. The main contribution of this thesis is that it provides comprehensive view not only of data quality itself, but also deals with the issues that are directly related to the corporate data quality assurance. This thesis can serve as a sort of guidance for one of the first implementation phases in the BI projects, which deals with the data integration, data consolidation and solving problems in the area of data quality.

This thesis deals with Business Intelligence and its testing. It seeks to highlight the differences from the classical software testing and finally design a methodology for BI solutions testing that could be used in practice on real projects of BI companies. The aim of thesis is to design a methodology for BI solutions testing based on theoretical knowledge of Business Intelligence and software testing with an emphasis on the specific BI characteristics and requirements and also in accordance with Clever Decision's requirements and test it in practice on a real project in this company. The paper is written up on the basis of studying literature in the field of Business Intelligence and software testing from Czech and foreign sources as well as on the recommendations and experience of Clever Decision's employees. It is one of the few if not the first sources dealing with methodology for BI solutions testing in the Czech language. This work could also serve as a basis for more comprehensive methodologies of BI solutions testing. The thesis can be divided into theoretical and practical part. The theoretical part tries to explain the purpose of Business Intelligence use in enterprises. It elucidates particular components of the BI solution, then the actual software testing, various types of tests, with emphasis on the differences and specificities of Business Intelligence. The theoretical part is followed by designed methodology for BI solutions using a generic model for the BI/DW solution testing. The practical part's highlight is the description of real BI project testing in Clever Decision according to the designed methodology.

This thesis deals with the application of Business Intelligence (BI) to support the corporate performance management in ISS Europe, spol. s r. o. This company provides licences and implements original software products as well as third-party software products. First, an analysis is conducted in the given company, which then serves as basis for the implementation of the BI solution that should be interconnected with the company strategies. The main goal is the implementation of a pilot BI solution to aid the monitoring and optimisation of corporate performance. Among secondary goals are the analysis of related concepts, business strategy analysis, strategic goals and systems identification and the proposition and implementation of a pilot BI solution. In its theoretical part, this thesis focuses on the analysis of concepts related to corporate performance and BI implementations and shortly describes the company together with its business strategy. The following practical part is based on the theoretical findings. An analysis of the company is carried out using the Balanced Scorecard (BSC) methodology, the result of which is depicted in a strategic map. This methodology is then supplemented by the Activity Based Costing (ABC) analytical method, which divides expenses according to assets. The results are informational data about which expenses are linked to handling individual developmental, implementational and operational demands for particular contracts. This is followed by an original proposition and the implementation of a BI solution which includes the creation of a Data Warehouse (DWH), designing Extract Transform and Load (ETL) and Online Analytical Processing (OLAP) systems and generating sample reports. The main contribution of this thesis is in providing the company management with an analysis of company data using a multidimensional perspective which can be used as basis for prompt and correct decision-making, realistic planning and performance and product optimisation.