Big amounts of data are produced every day in companies. By analyzing and visualizing the data a lot of insights can be gained. The company Solution Xperts wanted to create a system that could import and visualize Big Data. In this work a system was created and evaluated. The report shows that it can be difficult to visualize Big Data, but when a system is created it can easily be adapted to data coming from different companies and provide a lot of value to companies and organizations.

Responsive analytics are rapidly taking over the traditional data analytics dominated by the post-fact approaches in traditional data warehousing. Recent advancements in analytics demand placing analytical engines at the forefront of the system to react to updates occurring at high speed and detect patterns, trends and anomalies. These kinds of solutions find applications in Financial Systems, Industrial Control Systems, Business Intelligence and on-line Machine Learning among others. These applications are usually associated with Big Data and require the ability to react to constantly changing data in order to obtain timely insights and take proactive measures. Generally, these systems specify the analytical results or their basic elements in a query language, where the main task then is to maintain these results under frequent updates efficiently. The task of reacting to updates and analyzing changing data has been addressed in two ways in the literature: traditional business intelligence (BI) solutions focus on historical data analysis where the data is refreshed periodically and in batches, and stream processing solutions process streams of data from transient sources as flow (or set of flows) of data items. Both kinds of systems share the niche of reacting to updates (known as dynamic evaluation); however, they differ in architecture, query languages, and processing mechanisms. In this thesis, we investigate the possibility of a reactive and unified framework to model queries that appear in both kinds of systems. In traditional BI solutions, evaluating queries under updates has been studied under the umbrella of incremental evaluation of updates that is based on relational incremental view maintenance model and mostly focus on queries that feature equi-joins. Streaming systems, in contrast, generally follow the automaton based models to evaluate queries under updates, and they generally process queries that mostly feature comparisons of temporal attributes (e.g., timestamp attributes) along-with comparisons of non-temporal attributes over streams of bounded sizes. Temporal comparisons constitute inequality constraints, while non-temporal comparisons can either be equality or inequality constraints, hence these systems mostly process inequality joins. As starting point, we postulate the thesis that queries in streaming systems can also be evaluated efficiently based on the paradigm of incremental evaluation just like in BI systems in a main-memory model. The efficiency of such a model is measured in terms of runtime memory footprint and the update processing cost. To this end, the existing approaches of dynamic evaluation in both kind of systems present a trade-off between memory footprint and the update processing cost. More specifically, systems that avoid materialization of query (sub) results incur high update latency and systems that materialize (sub) results incur high memory footprint. We are interested in investigating the possibility to build a model that can address this trade-off. In particular, we overcome this trade-off by investigating the possibility of practical dynamic evaluation algorithm for queries that appear in both kinds of systems, and present a main-memory data representation that allows to enumerate query (sub) results without materialization and can be maintained efficiently under updates. We call this representation the Dynamic Constant Delay Linear Representation (DCLR). We devise DCLRs with the following properties: 1) they allow, without materialization, enumeration of query results with bounded-delay (and with constant delay for a sub-class of queries); 2) they allow tuple lookup in query results with logarithmic delay (and with constant delay for conjunctive queries with equi-joins only); 3) they take space linear in the size of the database; 4) they can be maintained efficiently under updates. We first study the DCLRs with the above-described properties for the class of acyclic conjunctive queries featuring equi-joins with projections and present the dynamic evaluation algorithm. Then, we present the generalization of thiw algorithm to the class of acyclic queries featuring multi-way theta-joins with projections. We devise DCLRs with the above properties for acyclic conjunctive queries, and the working of dynamic algorithms over DCLRs is based on a particular variant of join trees, called the Generalized Join Trees (GJTs) that guarantee the above-described properties of DCLRs. We define GJTs and present the algorithms to test a conjunctive query featuring theta-joins for acyclicity and to generate GJTs for such queries. To do this, we extend the classical GYO algorithm from testing a conjunctive query with equalities for acyclicity to test a conjunctive query featuring multi-way theta-joins with projections for acyclicity. We further extend the GYO algorithm to generate GJTs for queries that are acyclic. We implemented our algorithms in a query compiler that takes as input the SQL queries and generates Scala executable code – a trigger program to process queries and maintain under updates. We tested our approach against state of the art main-memory BI and CEP systems. Our evaluation results have shown that our DCLRs based approach is over an order of magnitude efficient than existing systems for both memory footprint and update processing cost. We have also shown that the enumeration of query results without materialization in DCLRs is comparable (and in some cases efficient) as compared to enumerating from materialized query results.

This master thesis explores the transformative potential of Large Language Models (LLMs) in enhancing business processes across various industries, with a specific focus on Management Innovation. As organizations face the pressures of digitalization, LLMs emerge as powerful tools that can revolutionize traditional business workflows through enhanced decision-making, automation of routine tasks, and improved operational efficiency. The research investigates the integration of LLMs within four key business domains: Human Resources, Tender Management, Consultancy, and Compliance. It highlights how LLMs facilitate Management Innovation by enabling new forms of workflow automation, data analysis, and compliance management, thus driving substantial improvements in efficiency and innovation. Employing a mixed-method approach, the study combines an extensive literature review with surveys and interviews with industry professionals to evaluate the impact and practical applications of LLMs. The findings reveal that LLMs not only offer significant operational benefits but also pose challenges related to data security, integration complexities, and privacy concerns. This thesis significantly contributes to the academic and practical understanding of LLMs, proposing a framework for their strategic adoption to foster Management Innovation. It underscores the need for businesses to align LLM integration with both technological capabilities and strategic business objectives, paving the way for a new era of management practices shaped by advanced technologies. / Denna masteruppsats utforskar den transformativa potentialen hos Stora Språkmodeller (LLMs) i att förbättra affärsprocesser över olika industrier, med särskilt fokus på Management Innovation. När organisationer möter digitaliseringens press, framträder LLMs som kraftfulla verktyg som kan revolutionera traditionella affärsarbetsflöden genom förbättrat beslutsfattande, automatisering av rutinuppgifter och förbättrad operationell effektivitet. Forskningen undersöker integrationen av LLMs inom fyra centrala affärsområden: Human Resources, Anbudshantering, Konsultverksamhet och Regelefterlevnad. Den belyser hur LLMs underlättar Management Innovation genom att möjliggöra nya former av arbetsflödesautomatisering, dataanalys och efterlevnadshantering, vilket driver påtagliga förbättringar i effektivitet och innovation. Genom att använda en blandad metodansats kombinerar studien en omfattande litteraturöversikt med enkäter och intervjuer med branschproffs för att utvärdera påverkan och praktiska tillämpningar av LLMs. Resultaten visar att LLMs inte bara erbjuder betydande operationella fördelar utan även medför utmaningar relaterade till datasäkerhet, integrationskomplexitet och integritetsfrågor. Denna uppsats bidrar avsevärt till den akademiska och praktiska förståelsen av LLMs, och föreslår en ram för deras strategiska antagande för att främja Management Innovation. Den understryker behovet för företag att anpassa LLM-integrationen med både teknologiska kapabiliteter och strategiska affärsmål, vilket banar väg för en ny era av ledningspraxis formad av avancerade teknologier.

在有限的資源之下，各區域地方政府相當渴望跳脫僵化與官僚的決策模式，尋求創新有效率的治理機制，另一方面開放政府資料已為國際化的趨勢，台灣於開放資料領域耕耘成果亦相當豐碩。本研究希望建置商業智慧平台，將開放資料轉換為無形的「智慧資本」，持續驅動創新有效率的「治理機制」，進而改善在地人民的生活品質。 本論文研究實作一網頁為基礎的商業智慧分析平台，工具包括資料包絡分析法、競爭者分析，透過探索式資料分析，使用者彈性操作指標與決策參數，反覆進行資料探索分析，進而了解（一）地方之競爭縣市與區域特色（二）各縣市相對治理績效（三）單一縣市之優勢產業。並藉由宜蘭縣的文創、觀光、環境此三個產業面向的資料為例說明。 本論文聚焦於使用前端框架技術—AngularJS之系統實作，藉由資料視覺化設計、提升使用者經驗，建置高擴充性的資料探勘分析的平台，更可滿足使用者一次購足的統計資料查詢環境。 / Facing the challenges of limited resources and budget constraints, regional governments have been actively pursuing strategies to transform conventional bureaucratic decision-making model into innovative and efficient governance mechanism. At the same time, “open government data” is becoming a political commitment for many countries and Taiwanese government has made significant advances in this respect recently. To leverage the trend for open public data, this thesis aims to develop a web-based business intelligence system to support efficient governance through in-depth analysis of intellectual capital. The tools provided in this system include data envelopment analysis (DEA), competitor identification, and exploratory data analysis. The system is designed to allow average users to experiment with different parameter settings and view the results interactively. Insights on competing counties and regional characteristics, relative governance efficiency and leading industry can be gained with ease. We illustrate the functionalities of the system using data from Yi-Lan County and investigate its competitiveness in three areas, namely, culture and creative industry, tourism, and environmental industry. AngularJS, a front-end framework, is utilized to implement the proposed business intelligence system. The objective is to provide a one stop shopping service for interactive data analysis and visualization with user friendly design and good extensibility.

While several U. S. firms have invested in Knowledge Management (KM) tools and software, it has become apparent that investments must be made in additional facets of KM, such as knowledge sharing (KS), thought by many researchers to be the most important component of KM. Of the two types of KS, explicit and tacit, the sharing of tacit knowledge has been shown to contribute the most to an organization’s performance. However, since tacit knowledge is difficult to both convey and acquire, this unshared tacit knowledge may ultimately harm an organization when, without the appropriate knowledge, individuals cannot effectively perform their professional responsibility. Although research has been conducted on the motivators that contribute to the sharing of tacit knowledge, the research has been conflicting. These inconsistencies could conceivably stem from measuring KS as a single factor rather than as separate components. The purpose of this study was two-fold, first to discover what motivators contributed to the sharing of tacit knowledge and second, to discover whether the sharing of knowledge when solicited differed from the sharing of knowledge when not solicited. Utilizing the Theory of Reasoned Action and Self-determination Theory as well as measuring the transfer of knowledge through externalization, as expressed by the SECI model, three research questions and 14 different hypotheses contributed to a survey instrument resulting in 370 usable survey responses. Employing confirmatory factor analysis and structural equation modeling, analysis of the data confirmed that a significant difference existed between the solicited and unsolicited sharing of tacit knowledge. This study found that measures for external, integrated, and intrinsic motivation differed among the two situational constructs of knowledge sharing. In addition, the study confirmed that a difference occurred between motivators and the two types of sharing when the sharing was mediated by a favorable attitude toward sharing.

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.

The literature presented in the following pages explores the shortcomings of the American public education system in the context of creating long-term, sustainable social change. Using financial illiteracy and its relationship to low quality of life as an entry point, the first section exposes public schools’ shortcomings as agents of social change by delving into the hardships endured by the original public school promoters of the 19th century, the pitfalls of President George W. Bush’s 2001 enactment of No Child Left Behind, and the shortcomings of the financial literacy programming that found traction in urban schools following the subprime lending crisis. These examples render the public education system unfit to address social change, at which point the paper segues into a discussion of social enterprise and the new field’s demonstrated potential to capture social value. After a brief historical exploration of social innovation which examines some values and principles of this “fourth sector,” successful ventures and failed social organizations are scrutinized in the penultimate chapter. The comparisons made ultimately argue in favor of social entrepreneurship’s fitness, on both a structural and ideological level, in addressing the complex social, environmental, and cultural issues of our time.

Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-07-12T16:11:01Z No. of bitstreams: 1 Mauricius Munhoz de Medeiros_.pdf: 3956183 bytes, checksum: b542e87eedac0be0bf8f79f48709672f (MD5) / Made available in DSpace on 2018-07-12T16:11:01Z (GMT). No. of bitstreams: 1 Mauricius Munhoz de Medeiros_.pdf: 3956183 bytes, checksum: b542e87eedac0be0bf8f79f48709672f (MD5) Previous issue date: 2018-02-27 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este estudo investigou o impacto das capacidades de inteligência analítica de negócios na expansão das capacidades cognitivas gerenciais, orientando a tomada de decisões (com base nos dados), de modo ágil (dinâmico), para a melhoria da gestão do desempenho organizacional. Explicou-se o fenômeno sob a perspectiva teórica das capacidades dinâmicas. Para a definição dos construtos, foram revisados, também, os elementos teóricos a respeito das capacidades de inteligência analítica de negócios e tomada de decisões. Executou-se uma pesquisa de métodos mistos, desenhada em duas etapas. A primeira, exploratória, realizada através de entrevistas com 10 gestores, permitiu o mapeamento dos relacionamentos e a identificação das variáveis, oportunizando o desenvolvimento do instrumento quantitativo. A segunda, confirmatória, realizada através de uma survey com 366 respondentes, cujos resultados foram analisados para validar o instrumento de pesquisa e mensurar o impacto por meio da modelagem de uma equação estrutural, confirmando-se 5 das 7 hipóteses definidas no modelo conceitual. O cerne da discussão está na explicação do impacto das capacidades de inteligência analítica de negócios na tomada decisões, onde os achados evidenciam impacto significativo das capacidades de inteligência analítica gerencial, governança e processamento de grandes dados, e analítica avançada de negócios. A pesquisa contribui para a teoria, por ter explicado as capacidades de inteligência analítica de negócios como capacidades dinâmicas, bem como pelo desenvolvimento e validação de um instrumento para a mensuração integrada dessas capacidades. Para o campo gerencial, o estudo aponta direcionamentos e recomendações ao indicar potencialidades e limitações para o desenvolvimento dessas capacidades. / This study investigated the impact of business analytical intelligence capabilities on the expansion of managerial cognitive capabilities, orienting decision making (based on data) in an agile (dynamic) way, to improve organizational performance management. The phenomenon was explained according to the theoretical perspective of dynamic capabilities. For the definition of the constructs, the theoretical elements regarding business analytical intelligence capabilities and decision making were also reviewed. A mixed-method research was carried out in two stages. The first, which was exploratory, was conducted through interviews with 10 managers and allowed the mapping of relationships and identification of variables, allowing the development of the quantitative instrument. The second, which was confirmatory, was performed through a survey with 366 interviewees, which results were analyzed to validate the research instrument and measure the impact through the modeling of a structural equation, confirming 5 of the 7 hypotheses defined in the conceptual model. The heart of the discussion lies in the explanation of the impact of business analytical intelligence capabilities on decision making, in which the findings evidence significant impact of managerial analytical intelligence capabilities, governance and the processing of big data, and advanced business analytics. This research contributes to the theory by explaining business analytical intelligence capabilities as dynamic capabilities, as well as by developing and validating an instrument for the integrated measurement of these capabilities. For the managerial field, this study points out directions and recommendations when indicating potentialities and limitations for the development of these capabilities.

Os sistemas de informação para inteligência de negócio (conhecidos também como BI - Business Intelligence) têm o propósito de coletar, estruturar, preparar e disponibilizar informações referentes aos processos internos e ao ambiente externo das organizações. O uso dessas informações visa suportar o processo de tomada de decisão bem como administração e inovação dos próprios processos de negócio das organizações. Dessa forma, essa classe de sistemas de informações (BI) tem o potencial de melhorar o desempenho individual e organizacional, sendo uma fonte de vantagem competitiva para as organizações. A abordagem de sistemas para BI não pode ser considerada somente como uma sequência de projetos isolados para disponibilização de informações. A gestão das demandas de informações necessárias para o negócio requer um esforço permanente para manter a função de BI alinhada com as necessidades da organização, através de processos que garantam a disponibilidade, o uso de informações e análises compartilhadas com base nos mesmos conceitos, documentação e organização das informações, assim como o suporte e treinamento técnico e funcional nos sistemas existentes. Nesse contexto, surgiu a proposta dos centros de competências de informações para BI, como uma estrutura de suporte para todas as áreas de negócio, sendo o elemento de ligação entre a área de tecnologia da informação e as diversas áreas da empresa para a gestão corporativa das informações. Este trabalho se propôs a operacionalizar uma forma de classificar as estruturas de gestão de informações para BI que são encontradas nas organizações, verificando o efeito de cada tipo de estrutura na qualidade percebida das informações disponibilizadas para as áreas de negócio, bem como o impacto para atividades dos indivíduos nas organizações que utilizam sistemas de BI. Foi realizada uma pesquisa quantitativa em três organizações, cada uma compondo uma amostra de cada tipo de estrutura de gestão de informações. Com a aplicação da técnica estatística de PLS, foi possível obter os efeitos entre as variáveis QI (Qualidade da informação), QGI (Qualidade da Gestão da Informação) e II (Impacto individual), moderados pelo tipo de estrutura de gestão de informações. Apesar de terem sido obtidas diferenças estatisticamente significantes entre as amostras, isto é, que as influências de QGI e QI em II variam estatisticamente de acordo com o tipo de estrutura de gestão de informações, foram pequenas as diferenças absolutas dos efeitos entre as estruturas adotadas em cada organização. Porém, os resultados obtidos nesta pesquisa de caráter exploratório sugerem a necessidade de estudos em uma maior quantidade de organizações, com vários casos para cada tipo de estrutura, a fim de identificar se existe consistência do efeito da variável moderadora nas variáveis analisadas entre diferentes tipos de organizações. / Information systems for business intelligence are designed to collect, organize, prepare and make available information related to internal processes and external environment of organizations. The use of this information is intended to support the process of decision making, business management and innovation of the processes of organizations. Thus, this class of information systems (BI) has the potential to improve individual and organizational performance, being a source of competitive advantage for organizations. The approach to deploy and sustain this class of information of system (BI) cannot be only a sequence of individual projects to make available information required during the scope phase of the project. Demand and delivery management of information necessary for the business requires an ongoing effort to maintain the function of BI aligned with the needs of the organization, through processes that ensure the information availability, use of shared information, information analysis across the organization based on the same concepts, documentation and organization of information, as well as support and training in technical and functional aspects of the systems. In this context, it has emerged the competence centers of information for BI, as a support organization for all areas of business, being the liaison between the area of information technology and the various areas of the company for corporate management of Information. This study proposes to operationalize a framework to classify the structures of information management for BI that are normally found in organizations and check the effect of each type of structure in the perceived quality of the information provided to the business areas as well the impact on individual activities for organizations that use BI systems. It was performed a quantitative study in three organizations, each one composing a sample of each type of management structure information. With the application of the statistical technique of PLS, it was possible to obtain the effects between variables QI (Quality of Information), QGI (Quality of Information Management) and II (Individual impact), moderated by the variable called \"type of information management structure\". Despite having been obtained statistically significant differences between the samples, in other words, that the influence of QGI and QI on II statistically vary according to the type of information management structure, the absolute differences of the effects were small between the respective structures adopted in each organization. However, the results obtained in this exploratory study suggest the need to research a larger number of organizations with multiple cases for each type of structure, in order to identify whether there is consistency in the effect of the moderating variable on the other variables among different types of organizations.

This research focuses on one of the least studied cultural dimension, “indulgence versus restraint” (IVR) and how it affects consumer behavior, international marketing, and global business operations in the U.S. and Mongolia. This project is the first research on IVR in Mongolia since the country is rarely studied and there is no available data for this cultural dimension. Samples of undergraduate business students (as consumers) from both countries were studied through surveys. The findings support that Mongolians and Americans are different regarding the “indulgence” cultural dimension. This paper has a significant contribution to the cross-cultural literature regarding the indulgence cultural dimension and its applications in global business and marketing and advertising strategies.