Introduction to Data Science

Data science = Interdisciplinary field using statistics, computing, and domain knowledge Turing Award = Award for contributions to the computing community Jim Gray = Imagined data science as a 'fourth paradigm' of science Data scientist = Professional combining programming code and statistical knowledge to derive insights from data

Unstructured data = Data lacking a predefined data model or is not organized in a pre-defined manner Empirical science = Based on observation or experience rather than theory or pure logic Informatics = Study of information processing, computer systems, and communication systems Domain knowledge = Knowledge specific to a particular field or subject area

Statistics = Utilized in data science to analyze actual phenomena with data Scientific computing = Used in data science to extract knowledge and insights from data Algorithms = Key component in data science for processing and analyzing data Workflow = Part of data science described as a method and discipline

<p>Client-side scripting = Used in web development for creating interactive web applications Multifaceted = Describes the complexity of data science as a profession and research paradigm Structured data = Data organized into a formatted repository such as a database Noisy data = Data with additional random or irrelevant information affecting its quality</p> Signup and view all the answers

<p>Mathematics = Field providing techniques and theories utilized in data science Information science = Field contributing to the interdisciplinary nature of data science Computer science = Field distinct from but related to data science and information science Natural sciences = Domain providing domain knowledge integrated into data science</p> Signup and view all the answers