A review and future direction of agile, business intelligence, analytics and data science

By D. Larson, Victor Chang. International Journal of Information Management, 2016

392 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/224eb3407b50533668b6c1caa55a720688b8b532

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Information Systems

1. Samar Al-Saqqa
2. Heba Abdelnabi
3. Samer Sawalha

Citations in the corpus

• Agile Software Development: Methodologies and Trends (2020, background): “The usability of the intensive documentation is one of the traditional development limitations [9], since writing and up-to-date synchronization of the documentations with the code is a time-consuming process especially if the requirements are changing very frequent.”
• Prescriptive analytics: Literature review and research challenges (2020, neutral): “Although there have been a lot of descriptive and predictive algorithms utilizing data mining, machine learning and artificial intelligence (Larson & Chang, 2016; Tsai et al., 2015), prescriptive analytics has not gathered the same attention yet.”