Analytics at Work: Smarter Decisions, Better Results
By T. Davenport, Jeanne Harris, R. Morison. 2010
503 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/78dcbbaf53b95e84e3b6c1f245514342e650cce0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Rodrigo Neves Calheiros
- Rajkumar Buyya
- Rajiv Kohli
- Clyde W. Holsapple
- Marcos Dias de Assunção
- Xixi Li
- Anita Lee-Post
- Arun Rai
Citations in the corpus
- Motivational Differences Across Post-Acceptance Information System Usage Behaviors: An Investigation in the Business Intelligence Systems Context (2013, background): “Organizations devote considerable resources and effort to implementing BIS to leverage their business value and enhance competitive advantage (Davenport et al. 2010, Negash and Gray 2008).”
- A unified foundation for business analytics (2014, background): “The framework devised later is offered as a unifying core for understanding the full scope of BA.”
- Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations (2014, unknown): “Further, analysts and managers today have available to them a powerful set of data analysis, data mining and data visualisation tools (Davenport and Harris 2007; Davenport et al. 2010).”
- Debating big data: A literature review on realizing value from big data (2017, background): “On the one hand, the development of analytics competency centres has been considered an effective approach to centralize resources in order to deal with the shortage of analytical skills (Davenport et al., 2010 in Sharma et al., 2014).”
- Digital innovation: A review and synthesis (2019, background): “, 2004), as well as a number of narratives documenting the use of business analytics among practitioners (Davenport et al., 2010).”
- Big Data computing and clouds: Trends and future directions (2013, background): “Although decision makers would like to base their decisions and actions on insights gained from this data [15], making sense of data, extracting non obvious patterns, and using these patterns to predict future behaviour are not new topics.”