Towards an Agile Framework for Business Intelligence Projects

Prouza, M.; Brodinova, Sarka; Tjoa, A. Min

doi:10.23919/mipro48935.2020.9245166

Cited by 3 publications

(3 citation statements)

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“…Three-pronged management approach: It is necessary to commit to a combination of the best ideas of each of the objective, data, and user management methodologies, creating triple management since these three approaches are considered to be perfectly compatible. [40] Agile approach: This approach can be considered novel in the area of software engineering and even more so in the area of business intelligence.…”

Section: Authormentioning

confidence: 99%

“…BI approaches RK BI HF DW SR [36], [37] The plan-oriented approach or requirement-oriented approach X X [36], [37] Focus on data management X X [36], [37] Focus on value chain data X X [36], [37] Process-based approach X X [36], [37] Event-driven approach X X [36], [37] Object-oriented approach X X [36], [37] Joint approach X [36], [37] Goal-oriented approach X X X X [36], [37] Model-based approach X X [36], [37] Adaptive business approach X X X X [38] Demand-driven or prototype-driven userbased [39] Three-pronged management approach (objective, data, and user management) X X X X [40] Agile approach X X X Second, a meta-analysis of more representative critical success factors was conducted. Critical success factors were weighted, ranked, and related to the methodologies that obtained the most approaches in the first analysis.…”

Section: Authormentioning

confidence: 99%

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Methodology for Business Intelligence Solutions in Internet Banking Companies

Viteri¹,

Cruzado²,

Huamán³

2022

International Journal on Advanced Science, Engineering and Information Technology

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Business intelligence in the banking industry has been studied extensively in the last decade; however, business executives still do not perceive efficiency in the decision-making process since the management and treatment of information are very timeconsuming for the deliverer, generating costs in the process. On the other hand, there is no formal methodology for developing business intelligence solutions in this sector. This work aims to optimize decision-making in a business unit that works with internet banking companies, reducing the time, the number of people, and the costs involved in decision-making. To meet the objective, basic and applied research was conducted. The basic research allowed the construction of a new methodology from a study of critical success factors and approaches from the business intelligence literature. The applied research involved the implementation of a business intelligence solution applying the new methodology in a pre-experimental study. Thirty decision-making processes were analyzed using pre-test and post-test data. Tools such as a stopwatch and observation were used to collect and record data on time spent, the number of people, and the decision-making costs. This information was processed in the specialized Minitab18 statistical software, which allowed the observation and confirmation of relevant results regarding time reduction, the number of people, and the costs generated. Therefore, it was concluded that the business intelligence solution, applying the new methodology, optimized decision making in the business unit that works with internet banking for companies.

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Section: Authormentioning

confidence: 99%

Section: Authormentioning

confidence: 99%

Methodology for Business Intelligence Solutions in Internet Banking Companies

Viteri¹,

Cruzado²,

Huamán³

2022

International Journal on Advanced Science, Engineering and Information Technology

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“…Successful BI projects tend to rely on a proficient Agile implementation, specifically during its initial stages, as it factors in critical elements essential for obtaining success [8]. This manuscript outlined the significance of integrating BI practices into Agile methodology, by categorizing Agile factors into several key groups that contribute to the success of BI development.…”

Section: Introductionmentioning

confidence: 99%

Systematic Literature and Expert Review of Agile Methodology Usage in Business Intelligence Projects

Wulandari,

Raharjo

2023

J. Inf. Syst. Eng. Bus. Intell.

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Background: Agile methodology is known for delivering effective projects with added value within a shorter timeframe, especially in Business Intelligence (BI) system which is a valuable tool for informed decision-making. However, identifying impactful elements for successful BI implementation is complex due to the wide range of Agile attributes. Objective: This research aims to systematically review and analyze the integration of BI within Agile methodology, providing valuable guidance for future projects implementation, enhancing the understanding of effective application, and identifying influential factors. Methods: Based on the Kitchenham method, 19 papers were analyzed from 288 papers, sourced from databases like Scopus, ACM, IEEE, and others published in 2016-2022. Meanwhile the extracted key factors impacting agile BI implementation were validated by qualified expert. Results: Agile was discovered to provide numerous benefits to BI projects by promoting flexibility, collaboration, and rapid iteration for enhanced adaptability, while effectively addressing challenges including those related to technology, management, and skills gaps. In addition, Agile methods, including tasks such as calculating cycle time, measuring defect backlogs, mapping code ownership, and engaging end users, offered practical solutions. The advantages included adaptability, success, value enhancement, cost reduction, shortened timelines, and improved precision. The research additionally considered other critical Agile elements such as BI tools, Agile Practices, Manifesto, and Methods, thereby enhancing insights for successful implementation. Conclusion: In conclusion, the research outlined Agile BI implementation into seven key factor groups, validated by qualified expert, providing guidance for BI integration and practices, and establishing a fundamental baseline for future applications. Keywords: Agile Methodology, Business Intelligence (BI), Expert Judgement, Kitchenham, Systematic Literature Review (SLR)

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