Data science involves the collection, management, processing, analysis, visualisation and interpretation of huge amounts of data. It is a multi-disciplinary field that integrates systematic thinking, methodology, process and technology to develop intelligence with respect to real-world problems. This paper focuses on the business environment and identifies the components of data science forming a conceptual architecture before proposing a composite data-driven process model. Representative tools and techniques are applied to relevant case studies demonstrating innovation in undergraduate programme design, customer analytics and the marketing of insurance.
CITATION STYLE
Lu, J. (2022). Data Science in the Business Environment: Architecture, Process and Tools. In Communications in Computer and Information Science (Vol. 1528 CCIS, pp. 279–293). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-95502-1_22
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