Business intelligence: an analysis of the literature

By Zack Jourdan, Rudolph Rainer, Thomas E. Marshall. IEEE Engineering Management Review, 2008

354 citations recorded by the source corpus.

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

Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges (2017, methodology): “BI analytics is adopted when the size of data is larger than the memory level, but in this case, data may be imported to the BI analysis environment [43].”
Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence (2014, methodology): “We analyzed the research questions, methodology and findings of these published papers and categorized them accordingly.”
Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation (2015, methodology): “The first (Jourdan et al., 2008) uses a traditional human effort approach, while the remaining three conducted TM literature analyses.”
The impact of business analytics on supply chain performance (2010, neutral): “It is therefore not surprising that research interest in BA use has been increasing [43].”
Business intelligence success: The roles of BI capabilities and decision environments (2013, background): “, 58] perspectives, some organizations fail to achieve BI success [50].”
Towards business intelligence systems success: Effects of maturity and culture on analytical decision making (2012, background): “They primarily support analytical decision-making [43] and are thus used in knowledge-intensive activities.”