The Effect of Business Intelligence on Management Accounting Information System

In today's business world, we are faced with high volumes of data. New developments in IT provide organizations with effective and efficient access and storage of information. In any case, there is a long distance between the mass of data and its use. Management accounting information system has changed as a key to success in today's business environment. In the field of management accounting, if the accounting information system is not capable of providing information to business managers timely and quickly, organizations' success will be threatened in the competitive environment. To cope with competitors and growth of long-term strategies, the accounting information system should benefit from business intelligence techniques to provide timely and effective financial information. The important competitive advantage against opponents and business competitors in the market is the most important reason to create intelligent systems. The purpose of business intelligence is to help control the flow and resources of business information within and around the organization. In this study, based on the research objectives, using a meta-analysis, some of the applied criteria and parameters of accounting information systems were examined based on business intelligence features. In addition, a model was proposed based on four categories of relationships and inferences, warning and reporting systems, and tools for effective analysis and decision-making. Among the criteria in the literature review are group decision-making, optimization, integration, simulation, traffic reports, prototyping based on the original version, two-way argument process, awareness technology, informing on the content, fuzzificatio, data mining, data storage, real-time analysis process, establishing communication  channels, creating intelligent factors etc. Therefore, the necessity to use a business intelligence-based model in management accounting information system is proposed

The Effect of Business Intelligence on Management Accounting Information System

In today's business world, we are faced with high volumes of data. New developments in IT provide organizations with effective and efficient access and storage of information. In any case, there is a long distance between the mass of data and its use. Management accounting information system has changed as a key to success in today's business environment. In the field of management accounting, if the accounting information system is not capable of providing information to business managers timely and quickly, organizations' success will be threatened in the competitive environment. To cope with competitors and growth of long-term strategies, the accounting information system should benefit from business intelligence techniques to provide timely and effective financial information. The important competitive advantage against opponents and business competitors in the market is the most important reason to create intelligent systems. The purpose of business intelligence is to help control the flow and resources of business information within and around the organization. In this study, based on the research objectives, using a meta-analysis, some of the applied criteria and parameters of accounting information systems were examined based on business intelligence features. In addition, a model was proposed based on four categories of relationships and inferences, warning and reporting systems, and tools for effective analysis and decision-making. Among the criteria in the literature review are group decision-making, optimization, integration, simulation, traffic reports, prototyping based on the original version, two-way argument process, awareness technology, informing on the content, fuzzificatio, data mining, data storage, real-time analysis process, establishing communication  channels, creating intelligent factors etc. Therefore, the necessity to use a business intelligence-based model in management accounting information system is proposed

A practical framework for assessing business intelligence competencies of enterprise systems using fuzzy ANP approach

As traditional concept in management, decision support had a remarkable role in competitiveness or survival of organisations and following, as modern impression, nowadays business intelligence (BI) has various applications in achieving desirable decision supports. Consequently, assessing BI competencies of enterprise systems can enable decision support in firms. This paper presents a practical framework for assessing the business intelligence capabilities of enterprise systems based on a set of novel factors and utilising fuzzy analytic network process (FANP). Through this, the construct of BI competency is decomposed into three main competency parts including ‘managerial’, ‘technical’ and ‘system enabler’ sub-goals, five main factors and 26 criteria. Using this framework, the BI competency level of enterprise systems can be determined which can help the decision makers to select the enterprise system that best suits organisations’ intelligence decision support needs. In order to validate the proposed model, it is applied to a real Iranian international offshore engineering and construction company in the oil industry to select and acquire ERP system. This research provides a complete frame (factors, criteria and procedures) for firms to assess their proposed software and systems in the field of BI competencies and functions

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and PortoInformation Technology has been one of drivers of the revolution that currently is happening in today’s management decisions in most organizations. The amount of data gathered and processed through the use of computing devices has been growing every day, providing a valuable source of information for decision makers that are managing every type of organization, public or private. Gathering the right amount of data in a centralized and unified repository like a data warehouse is similar to build the foundations for a system that will act has a base to support decision making processes requiring factual information. Nevertheless, the complexity of building such a repository is very challenging, as well as developing all the components of a data warehousing system. One of the most critical components of a data warehousing system is the Extract-Transform-Load component, ETL for short, which is responsible for gathering data from information sources, clean, transform and conform it in order to store it in a data warehouse. Several designing methodologies for the ETL components have been presented in the last few years with very little impact in ETL commercial tools. Basically, this was due to an existing gap between the conceptual design of an ETL system and its correspondent physical implementation. The methodologies proposed ranged from new approaches, with novel notation and diagrams, to the adoption and expansion of current standard modeling notations, like UML or BPMN. However, all these proposals do not contain enough detail to be translated automatically into a specific execution platform. The use of a standard well-known notation like Relational Algebra might bridge the gap between the conceptual design and the physical design of an ETL component, mainly due to its formal approach that is based on a limited set of operators and also due to its functional characteristics like being a procedural language operating over data stored in relational format. The abstraction that Relational Algebra provides over the technological infrastructure might also be an advantage for uncommon execution platforms, like computing grids that provide an exceptional amount of processing power that is very critical for ETL systems. Additionally, partitioning data and task distribution over computing nodes works quite well with a Relational Algebra approach. An extensive research over the use of Relational Algebra in the ETL context was conducted to validate its usage. To complement this, a set of Relational Algebra patterns were also developed to support the most common ETL tasks, like changing data capture, data quality enforcement, data conciliation and integration, slowly changing dimensions and surrogate key pipelining. All these patterns provide a formal approach to the referred ETL tasks by specifying all the operations needed to accomplish them in a series of Relational Algebra operations. To evaluate the feasibility of the work done in this thesis, we used a real ETL application scenario for the extraction of data in two different social networks operational systems, storing hashtag usage information in a specific data mart. The ability to analyze trends in social network usage is a hot topic in today’s media and information coverage. A complete design of the ETL component using the patterns developed previously is also provided, as well as a critical evaluation of its usage.As Tecnologias da Informação têm sido um dos principais catalisadores na revolução que se assiste nas tomadas de decisão na maioria das organizações. A quantidade de dados que são angariados e processados através do uso de dispositivos computacionais tem crescido diariamente, tornando-se uma fonte de informação valiosa para os decisores que gerem todo o tipo de organizações, públicas ou privadas. Concentrar o conjunto ideal de dados num repositório centralizado e unificado, como um data warehouse, é essencial para a construção de um sistema que servirá de suporte aos processos de tomada de decisão que necessitam de factos. No entanto, a complexidade associada à construção deste repositório e de todos os componentes que caracterizam um sistema de data warehousing é extremamente desafiante. Um dos componentes mais críticos de um sistema de data warehousing é a componente de Extração-Transformação- Alimentação (ETL) que lida com a extração de dados das fontes, que limpa, transforma e concilia os dados com vista à sua integração no data warehouse. Nos últimos anos têm sido apresentadas várias metodologias de desenho da componente de ETL, no entanto estas não têm sido adotadas pelas ferramentas comerciais de ETL principalmente devido ao diferencial existente entre o desenho concetual e as plataformas físicas de execução. As metodologias de desenho propostas variam desde propostas que assentam em novas notações e diagramas até às propostas que usam notações standard como a notação UML e BPMN que depois são complementadas com conceitos de ETL. Contudo, estas propostas de modelação concetual não contêm informações detalhadas que permitam uma tradução automática para plataformas de execução. A utilização de uma linguagem standard e reconhecida como a linguagem de Álgebra Relacional pode servir como complemento e colmatar o diferencial existente entre o desenho concetual e o desenho físico da componente de ETL, principalmente devido ao facto de esta linguagem assentar numa abordagem procedimental com um conjunto limitado de operadores que atuam sobre dados armazenados num formato relacional. A abstração providenciada pela Álgebra Relacional relativamente às plataformas de execução pode eventualmente ser uma vantagem tendo em vista a utilização de plataformas menos comuns, como por exemplo grids computacionais. Este tipo de arquiteturas disponibiliza por norma um grande poder computacional o que é essencial para um sistema de ETL. O particionamento e distribuição dos dados e tarefas pelos nodos computacionais conjugam relativamente bem com a abordagem da Álgebra Relacional. No decorrer deste trabalho foi efetuado um estudo extensivo às propriedades da AR num contexto de ETL com vista à avaliação da sua usabilidade. Como complemento, foram desenhados um conjunto de padrões de AR que suportam as atividades mais comuns de ETL como por exemplo changing data capture, data quality enforcement, data conciliation and integration, slowly changing dimensions e surrogate key pipelining. Estes padrões formalizam este conjunto de atividades ETL, especificando numa série de operações de Álgebra Relacional quais os passos necessários à sua execução. Com vista à avaliação da sustentabilidade da proposta presente neste trabalho, foi utilizado um cenário real de ETL em que os dados fontes pertencem a duas redes sociais e os dados armazenados no data mart identificam a utilização de hashtags por parte dos seus utilizadores. De salientar que a deteção de tendências e de assuntos que estão na ordem do dia nas redes sociais é de vital importância para as empresas noticiosas e para as próprias redes sociais. Por fim, é apresentado o desenho completo do sistema de ETL para o cenário escolhido, utilizando os padrões desenvolvidos neste trabalho, avaliando e criticando a sua utilização