Data science core knowledge and skills

The core knowledge base and skill sets for individual data roles need to cover descriptive, diagnostic, predictive and prescriptive levels of analytics and model development. Figure 1 illustrates the core categories of knowledge and skill that may be required for data innovation and services. They are theoretical foundation, technical skills, work practices, communication, and management.

  • Creative thinking, to support the data science objective of “think with data”, which requires knowledge and skills in cognitive thinking, imaginary thinking, inferential thinking, reduction, abstraction, and summarization, as well as research methods and decision sciences.
  • Theoretical foundation, consisting of knowledge of relevant theories in disciplines and areas that include statistics, mathematics, understanding data characteristics, data representation and modeling, similarity and metric learning, algorithms and models, qualitative analysis, quantitative analysis, computing/computational science, complexity analysis, evaluation methods and enhancement, meta-analysis and meta-synthesis.
  • Technical skills, composed of skills and techniques in data preparation, data exploration, data mining, machine learning, pattern recognition, information retrieval, data management, data engineering, analytics programming, high performance computing, networking and communication, operations research, human-machine interaction, visualization and graphics, software engineering, system analysis and design.
  • Practices, including components of business analytics, experimental design, project development, case studies, applications, and capstone projects.
  • Communication, consisting of presentation, story-telling, reporting, documentation, group collaboration, teamwork, seminars and workshops, reflection, and refinement.
  • Management of governance, organization, projects, resources, roles, responsibilities, risk, impact, privacy, security, social and professional issues, and deployment and decisions.

Data science knowledge and capability set

Figure 1: Data science knowledge and capability set.

 

Note: Excerpted from “Longbing Cao. Data Science: Profession and Education

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