What Is Data Science
By Longbing Cao. 2018
568 citations recorded by the source corpus.
Subfields: Information Systems and Management, Management Information Systems, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/d9a984e15b1a86a66ecbac9e66d458dae4cb616c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems and Management
- John Krogstie
- Cèsar Ferri
- Paul A. Pavlou
- Ilias O. Pappas
- Patrick Mikalef
- José Ramón Saura
- Peter A. Flach
- Tamara Dinev
In Management Information Systems
- Patrick Mikalef
- John Krogstie
- Ilias O. Pappas
- Paul A. Pavlou
- José Ramón Saura
- Peter A. Flach
- Chao-Hsing Lee
- Chien-Wen David Chen
In Management Science and Operations Research
- John Krogstie
- Paul A. Pavlou
- Ilias O. Pappas
- Patrick Mikalef
- José Ramón Saura
- Peter A. Flach
- Meelis Kull
- Tao Zhou
Citations in the corpus
- Using Data Sciences in Digital Marketing: Framework, methods, and performance metrics (2020, background): “Data science: theoretical framework Overall, the major goal of DS is to extract knowledge from data analysis to answer specific research questions (Kelleher & Tierney, 2018).”
- Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities (2020, background): “Such capabilities can, in turn, enable firms to seize emerging opportunities or avoid threats through real-time process orchestration [87], dynamic resource allocation, and financial risk assessment [92,93].”
- CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories (2021, background): “[65], [66], [67], [68], and they are usually associated with the exploration activities.”