Data Science: Fundamental Principles
Data Science: Fundamental Principles
Abstract
We live in a world where we collect huge amounts of data. Traditional methods and techniques are no longer sufficient to process them. In addition to the sophisticated development of computers, new ways of processing data are evolving. Data Science is a new emerging multidisciplinary field that combines classical disciplines like statistics and mathematics with computer science. The main goal of Data Science is to turn large sets of both unstructured and structured data into useful information that can help organisations to make powerful data-driven decisions. At a high level, data science can be described as a set of fundamental ...
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main problem is not how to collect data, but how to extract useful information from them. There are many powerful tools for data scientist that can help them in this process, but in order to use them wisely, data scientists must have much pre-knowledge from statistics, math and computer sciences, and they also need to be able to see business problems from a data perspective. There are a different definitions of data science ("data science is a set of fundamental principles that support and guide the principled extraction of information and knowledge from data" (Provost and Fawcett, 2013), "data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data" (Dhar, 2013), "data science is an amalgamation of classical disciplines like statistics, data mining, databases, and distributed systems"(Van der Aalst, 2016)), but they all have in common that Data Science is a ...
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International Association for Statistical Computing was founded and their mission was to integrate traditional statistical methodology, modern computer technology and domain experts' knowledge to transform data into information. In Mining Data for Nuggets of Knowledge (Zahavi, 1999), author pointed out that traditional statistical methods work well with small data sets, but to handle the massive amounts of data, new tools have to be developed. Data Science Journal began to publish in 2002 and in 2008 "Data Scientist" became a buzzword, mostly by DJ Patil and Jeff Hammerbacher (Foote, 2016). In 2011, new concept of Data Lakes was introduced. Data Lakes store information using a ...
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"Data Science: Fundamental Principles." Essayworld.com. Essayworld.com, 9 Jul. 2020. Web. 23 Dec. 2024. <http://www.essayworld.com/essays/Data-Science-Fundamental-Principles/107390>
"Data Science: Fundamental Principles." Essayworld.com. July 9, 2020. Accessed December 23, 2024. http://www.essayworld.com/essays/Data-Science-Fundamental-Principles/107390.
"Data Science: Fundamental Principles." Essayworld.com. July 9, 2020. Accessed December 23, 2024. http://www.essayworld.com/essays/Data-Science-Fundamental-Principles/107390.
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