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Questions and Answers
What is data science?
What is data science?
Data science is an interdisciplinary academic field that uses statistics, scientific computing, and systems to extract knowledge from data.
What does data science integrate?
What does data science integrate?
Data science integrates domain knowledge from underlying application domains such as natural sciences, information technology, and medicine.
How can data science be described?
How can data science be described?
Data science can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.
What does data science aim to understand and analyze?
What does data science aim to understand and analyze?
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How is data science different from computer science and information science?
How is data science different from computer science and information science?
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Study Notes
Definition of Data Science
- Data science is an interdisciplinary academic field that combines statistics, scientific computing, scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Characteristics of Data Science
- Data science integrates domain knowledge from underlying application domains (e.g., natural sciences, information technology, and medicine).
- Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.
Scope of Data Science
- Data science aims to unify statistics, data analysis, informatics, and related methods to understand and analyze actual phenomena using data.
- Data science draws techniques and theories from mathematics, statistics, computer science, information science, and domain knowledge.
Distinction from Other Fields
- Data science is distinct from computer science and information science.
- Turing Award winner Jim Gray envisioned data science as a unique field.
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Description
Test your knowledge of data science with this quiz! Explore statistics, scientific computing, algorithms, and more, and see how well you understand the interdisciplinary field of data science.
