Evaluating Open Source Business Intelligence Tools using OSSpal Methodology

Ferreira, Tânia; Pedrosa, Isabel; Bernardino, Jorge

doi:10.5220/0006516402830288

Cited by 7 publications

(3 citation statements)

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“…From 2017 to 2019 several papers used the OSSpal methodology in different research areas, such as Business Intelligence Tools [11], [12], Data Mining Tools [13], Ecommerce Tools [14], Project Management Tools [15]- [18], and NoSQL databases [19]. These works used the same implementation and analyzed three or four tools.…”

Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Data Modeling Design Tools

et al. 2022

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Conceptual modeling describes the physical or social aspects of the world abstractly, encompassing the interpretation of data production, gathering, visualization, and analysis. The quality of the data analysis system will limit the excellence of any decision-making process. Thus, accurately specifying the physical data model is essential. The primary goal of our work is to compare tools that can create this physical model. We recognize several types of data models, but we only include the relational data model. We evaluate free and commercial data modeling tools. But it is challenging to decide how to compare them and which elements are crucial. We propose a new approach for software tools' evaluation based on the Business Readiness Rating (BRR) model and the OSSpal evaluation methodology. In this work, we show that this new methodology can be tailored to the needs of each individual developer or team, thus providing proper and meaningful results. Also, by applying this hybrid approach to the evaluation of data modelling tools, we show it can robustly handle the bias from lesser relevant evaluation categories.

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Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Data Modeling Design Tools

et al. 2022

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“…A título de conclusão pode-se referir que a iniciativa da IES em estudo relativamente à adesão ao Twitter tem como vantagem permitir uma maior consciencialização sobre o trabalho de outros académicos, possivelmente auxiliando o pensamento multidisciplinar ou a introdução de ideias fora de seu próprio domínio [28], assim como a promoção da IES analisada e, desta forma, entende-se que estão a ser cumpridos os objetivos. Contudo existem pontos nestes processos suscetíveis de melhoria e as ferramentas de Business Intelligence podem fornecer os insights necessários [29].…”

Section: Conclusão E Trabalho Futurounclassified

Twitter Sensitivity Analysis in a Higher School Using Power BI

Varela

Bernardino

Pedrosa

2020

2020 15th Iberian Conference on Information Systems and Technologies (CISTI)

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Resumo -O Twitter, enquanto rede social, adquire especial importância nas instituições académicas, como é exemplo das Instituições de Ensino Superior (IES). Esta ferramenta permite às instituições, não só divulgar o seu trabalho e conhecer o feedback da comunidade quanto ao mesmo, mas também manter contacto com a sua rede alumini e fomentar conversações entre a comunidade académica. Neste trabalho elaborou-se um dashboard com os últimos 39 Tweets, relacionados com esta IES, com recurso à ferramenta de visualização de dados Power BI. Desta análise pode-se aferir que os utilizadores não utilizam o Twitter do com o intuito de debater ideias e colaborar, mas apenas para temas relacionados com atividades de lazer académico. Este dashboard permite perceber o que está a ser dito sobre esta IES no Twitter e de que forma se pode melhorar a utilização desta plataforma de comunicação.

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“…In the last decade, with a paradigm shift in the way software components communicate with each other, suppliers have developed, a new generation of BI components have been developed with interoperability in mind and hence could be easily integrated. There are a number of open source BI platforms and these have been reviewed and evaluated by Lapa [31] and Ferreira [30]. The BIRT technology Platform [32] allows the creation of data visualizations and reports that can be embedded into other applications, particularly those that have been developed in Java or Java EE.…”

Section: Bi Solutionsmentioning

confidence: 99%

Empowering SMEs to Make Better Decisions with Business Intelligence: A Case Study

Raj¹,

Wong

Beaumont

2018

Communications in Computer and Information Science

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With the advance of Business Information Systems (BIS), irrespective of the size, companies have adopted an approach to electronic data collection and management for two decades. The advancement in technology means they have in their possessions large volumes of historical data. Large organizations have cached on this and use a range of tools and techniques to leverage the usefulness of this information to make more informed business decisions. For most small and medium-sized enterprises (SMEs), however, such data typically sits in an archive without being utilized. While SMEs appreciate the need for utilizing historical data to make more informed business decisions, they often lack the technical knowhow and funding to embrace an effective BI solution. In this paper, drawing from our experience in implementing a BI solution for a UK SME we discuss some potential tools and strategies that could help SMEs overcome these challenges so as to reap the benefits of adopting an effective BI solution.

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Evaluating Open Source Business Intelligence Tools using OSSpal Methodology

Cited by 7 publications

References 0 publications

Comparative Analysis of Data Modeling Design Tools

Comparative Analysis of Data Modeling Design Tools

Twitter Sensitivity Analysis in a Higher School Using Power BI

Empowering SMEs to Make Better Decisions with Business Intelligence: A Case Study

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