Empowering End-users to Collaboratively Manage and Analyze Evolving Data Models

In order to empower end-users to make well-founded decisions based on domain-specific knowledge, companies use end-user oriented business intelligence (BI) software like spreadsheets. Moreover, many decisions require the collaboration of multiple and autonomous knowledge workers. However, prevalent BI software does not provide elevated collaboration features as known from traditional Web 2.0 technologies. There is also a lack of research on how to integrate collaboration features into BI systems, and which challenges arise as a consequence. In the paper at hand we address this issue by proposing the Spreadsheet 2.0 approach, which integrates Web 2.0 features with the spreadsheet paradigm as most-common representative of end-user-oriented business intelligence tools. Therefore, we derive requirements for a Web 2.0-based approach to collaborative BI, and present the conceptual design for a Spreadsheet 2.0 solution. Subsequently, we demonstrate a corresponding prototypical implementation, and elaborate on key findings and main challenges identified by its application and evaluation

A Self-Service Supporting Business Intelligence and Big Data Analytics Architecture

Self-service Business Intelligence (SSBI) is an emerging topic for many companies. Casual users should be enabled to independently build their own analyses and reports. This accelerates and simplifies the decision-making processes. Although recent studies began to discuss parts of a self-service environment, none of these present a comprehensive architecture. Following a design science research approach, this study proposes a new self-service oriented BI architecture in order to address this gap. Starting from an in-depth literature review, an initial model was developed and improved by qualitative data analysis from interviews with 18 BI and IT specialists form companies across different industries. The proposed architecture model demonstrates the interaction between introduced self-service elements with each other and with traditional BI components. For example, we look at the integration of collaboration rooms and a self-learning knowledge database that aims to be a source for a report recommender

An ontology-based approach to Automatic Generation of GUI for Data Entry

This thesis reports an ontology-based approach to automatic generation of highly tailored GUI components that can make customized data requests for the end users. Using this GUI generator, without knowing any programming skill a domain expert can browse the data schema through the ontology file of his/her own field, choose attribute fields according to business\u27s needs, and make a highly customized GUI for end users\u27 data requests input. The interface for the domain expert is a tree view structure that shows not only the domain taxonomy categories but also the relationships between classes. By clicking the checkbox associated with each class, the expert indicates his/her choice of the needed information. These choices are stored in a metadata document in XML. From the viewpoint of programmers, the metadata contains no ambiguity; every class in an ontology is unique. The utilizations of the metadata can be various; I have carried out the process of GUI generation. Since every class and every attribute in the class has been formally specified in the ontology, generating GUI is automatic. This approach has been applied to a use case scenario in meteorological and oceanographic (METOC) area. The resulting features of this prototype have been reported in this thesis

Self-service business intelligence and analytics application scenarios: A taxonomy for differentiation

Self-service business intelligence and analytics (SSBIA) empowers non-IT users to create reports and analyses independently. SSBIA methods and processes are discussed in the context of an increasing number of application scenarios. However, previous research on SSBIA has made distinctions among these scenarios only to a limited extent. These scenarios include a wide variety of activities ranging from simple data retrieval to the application of complex algorithms and methods of analysis. The question of which dimensions are suitable for differentiating SSBIA application scenarios remains unanswered. In this article, we develop a taxonomy to distinguish among SSBIA applications more effectively by analyzing the relevant scientific literature and current SSBIA tools as well as by conducting a case study in a company. Both researchers and practitioners can use this taxonomy to describe and analyze SSBIA scenarios in further detail. In this way, the opportunities and challenges associated with SSBIA application can be identified more clearly. In addition, we conduct a cluster analysis based on the SSBIA tools thus analyzed. We identify three archetypes that describe typical SSBIA tools. These archetypes identify the application scenarios that are addressed most frequently by SSBIA tool providers. We conclude by highlighting the limitations of this research and suggesting an agenda for future research

Understanding Continuous Use of Business Intelligence Systems: A Mixed Methods Investigation

Business intelligence (BI) systems play an important role in organizations’ decision-making processes. The existing literature has long focused on the continuous use of information systems (IS). However, the specificities of BI systems such as voluntary use, long-term return of investments, heterogeneity of their use cases, and innovative rather than routine use in such systems motivate our investigating continuous use in the specific context of BI systems. To theorize continuous use of BI systems, we investigate the influencing factors and their interactions. By means of an exploratory and confirmatory mixed-methods research design that comprises a literature review, a single-case study, and a survey, we integrate the identified factors and hypothesize their influence on the continuous use of BI systems in a research model. We test the research model following a partial least squares (PLS) approach to structural equation modeling (SEM). The paper makes two primary contributions: 1) it confirms certain well-established constructs and relations in the specific context of BI systems, which are generally theorized for the continuous use of IS, and 2) it introduces either new constructs or new relations through the given investigation in the context of BI systems. Future studies can test these new constructs and relations as potential input for theorizing general IS continuous use

Benefits and barriers of self-service business intelligence implementation in micro-enterprises: a case of ABC Travel & Consulting

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementSmall medium enterprises (hereinafter: SME) represent 99.8 % of firms in the non-financial business sector of the European Union. SME’s cover three different types of companies, namely micro-, small- and medium-sized enterprises. Micro-enterprises are the most common type of SME in the European Economic Area, accounting for 93.2 % of the non-financial business sector (Muller, Julius, Herr & Peycheva, 2017). Due to their importance, the focus of this work will be on micro-enterprises. They are defined by two factors: firstly, the number of employees has to be lower than ten, and secondly, the turnover or the total assets must be lower than or equal to two million Euros (European Commission, 2014). Business intelligence systems (hereinafter: BIS) have become significantly important in the business world and academic community over the last two decades (Chen, Chiang & Storey, 2012). The global revenue reached a volume of $18.3 billion in 2017 and is forecasted to reach$22.8 billion by the end of 2020. Modern BIS continue to expand more rapidly than the overall market (Moore, 2017). The benefits of the integration of BIS can be seen longterm, users are typically decision makers at higher organizational levels (Puklavec, Oliveira & Popovic, 2014). With the usage of BIS, knowledge workers such as executives, managers, and analysts can make better and faster decisions (Chaudhuri, Dayal & Narasayya, 2011). The proper usage of BIS can be seen as a prerequisite for business success, but these tools are often complex and require a high level of expertise to work with (Davenport, 2017). It is a challenge for micro companies to implement BIS because they have often only a limited set of financial and human resources (Puklavec, Oliveira & Popovic, 2014)

Uma interface baseada em conhecimento para interação com data warehouses espaciais

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-graduação em Ciência da Computação, Florianópolis, 2010A análise de informação em um data warehouse espacial (SDW) pode envolver o manuseio de grandes volumes de dados espaciais. Usuários de domínios específicos de aplicação, com habilidades básicas de computação, são geralmente incapazes ou têm sérias dificuldades para resolver suas necessidades de análise de informação interagindo diretamente com SDWs, embora alguns sejam capazes de interagir com data warehouses (DW) convencionais através de uma interface gráfica (GUI). As dificuldades são maiores em um SDW que em um DW convencional, entre outras razões, pela variedade e complexidade dos dados espaciais, operadores espaciais e funções de agregação espacial utilizadas para especificar consultas SOLAP. Este trabalho propõe um sistema baseado em conhecimento, chamado de S2DW (Semantic and Spatial Data Warehouses), para auxiliar estes usuários de domínios específicos a efetuar análises de informação em SDWs, acessando descrições semânticas dos data marts espaciais através de uma interface gráfica baseada em conhecimento (GUI). Este trabalho descreve a arquitetura geral do S2DW e foca em sua GUI. A interface gráfica baseada em conhecimento do S2DW permite ao usuário pesquisar data marts relacionados a um determinado assunto, através da especificação de palavras-chave ou pela navegação em uma visão de uma ontologia do domínio. Cada data mart relacionado ao assunto pesquisado é apresentado ao usuário como um grafo representando a estrutura dimensional do cubo de informação. Este grafo é semanticamente enriquecido com descrições do conteúdo dos dados e dos recursos de processamento de dados do data mart espacial. Consultas espaciais OLAP podem ser especificadas interagindo com a interface gráfica baseada em conhecimento, a qual orienta o usuário a compor adequadamente operadores e funções para tratar os diferentes tipos de dados disponíveis no data mart, visando atender diferentes necessidades de análise. As tabelas, gráficos e mapas fornecidos como resposta as consultas SOLAP também permitem a interação do usuário para gradualmente refinar a análise da informação. As principais contribuições deste trabalho são a proposta inicial da GUI baseada em conhecimento do S2DW e o teste de usabilidade desta GUI, em um estudo de caso com usuários reais do domínio agrícola

Conem: um modelo para representação e análise de informação de redes espaciais em data warehouses

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-graduação em Ciência da Computação, Florianópolis, 2011Um Data Warehouse Espaço-Temporal (DWET) manipula concomitantemente dados convencionais, espaciais e temporais. Uma necessidade ainda não atendida pela tecnologia de DWET é o suporte à análise de informação de redes complexas de elementos espaciais. Neste sentido, este trabalho propõe um modelo para a análise de redes complexas em DWET. Inspirado em ideias da Geografia, este modelo tem por objetivo representar a estrutura da rede e os estados dos elementos que a compõem, para suportar a análise da evolução do estado de diferentes porções da rede ao longo do tempo. O modelo proposto utiliza ontologias para descrever hierarquias de tipos de elementos da rede, baseadas em conceitualizações específicas do domínio de aplicação, além de ontologias sobre partições do espaço e do tempo. Dimensões de datamarts podem ser geradas a partir de visões dessas ontologias, para contemplar necessidades de análise específicas. O modelo proposto estende um modelo dimensional espaço-temporal para suportar OLAP espacial (SOLAP) com os elementos da rede, usando dimensões de análise definidas de acordo com hierarquias contidas nas ontologias. Ele também define um operador denominado Trace para permitir a análise da evolução do estado dos componentes de porções da rede, selecionadas de acordo com as dimensões de análise definidas para o datamart. O modelo proposto foi implementado em um protótipo. A interface gráfica, baseada em tabelas e mapas, está integrada ao módulo SOLAP. Ao navegar pelos mapas e tabelas apresentando resultados de operações SOLAP, outras operações SOLAP podem ser invocadas e os resultados apresentados em novos gráficos e tabelas. Um slider permite a análise da evolução temporal do estado de porções da rede. Por fim, a modelo é avaliado em um estudo de caso do setor elétrico, o qual possibilita a investigação de padrões e tendências espaço-temporais em diferentes porções de uma rede de distribuição de energia elétrica

Technical capabilities of business intelligence systems in South African medium to large organisations

Magister Commercii (Information Management) - MCom(IM)Companies are putting in place systems that might assist in attaining their business goals and vision to improve the running of their business processes. Companies are looking at Business Intelligence (BI) as a means to attain a competitive edge over competitors, predict future trends, improve strategic decision making, facilitate quick and reliable decision making, or make the day-to-day running of business easier. The study looks at the perspective of middle to top management on the context of BI, with main focus on the technical capabilities of BI within medium to large companies in South Africa. To obtain factors relevant to the South African business context, an online survey was conducted with various sectors of South African industry. The study is part of research conducted collaboratively by the University of the Western Cape and Neu-Ulm University of Applied Sciences in Germany. It focuses on exploring usage of Business Intelligence Systems (BIS) together with Corporate Performance. Online surveys were conducted that targeted medium to large companies in Germany and South Africa by questioning middle to top management on issues surrounding BIS and Corporate Performance. On this basis online survey approach was taken to ensure required number of participants would be covered and approached. Therefore, the research adopted stratified sample method for the online survey. Stratified sampling enabled the expansion of the research by gathering and collaborating participants responses on the research question and eliminate the possibilities of unreliable sample from large population

Technical capabilities of Business Intelligence systems in South African medium to large organisations

Magister Commercii (Information Management) - MCom(IM)Companies are putting in place systems that might assist in attaining their business goals and vision to improve the running of their business processes. Companies are looking at Business Intelligence (BI) as a means to attain a competitive edge over competitors, predict future trends, improve strategic decision making, facilitate quick and reliable decision making, or make the day-to-day running of business easier. The study looks at the perspective of middle to top management on the context of BI, with main focus on the technical capabilities of BI within medium to large companies in South Africa. To obtain factors relevant to the South African business context, an online survey was conducted with various sectors of South African industry. The study is part of research conducted collaboratively by the University of the Western Cape and Neu-Ulm University of Applied Sciences in Germany. It focuses on exploring usage of Business Intelligence Systems (BIS) together with Corporate Performance. Online surveys were conducted that targeted medium to large companies in Germany and South Africa by questioning middle to top management on issues surrounding BIS and Corporate Performance. On this basis online survey approach was taken to ensure required number of participants would be covered and approached. Therefore, the research adopted stratified sample method for the online survey. Stratified sampling enabled the expansion of the research by gathering and collaborating participants responses on the research question and eliminate the possibilities of unreliable sample from large population