Abstract
In today's digital world, with the exponential growth of data, new approaches to aggregate and analyze data are bringing considerable benefits to many fields, such as healthcare, Internet of Things, social media, business, and public policy. Data science (DS) is considered as an interdisciplinary field that covers how data is prepared, analyzed, interpreted, modeled, and presented. It is a combination of data analytics, machine learning, math, and statistics, as well as domain and business knowledge. One of the main goals of DS is to leverage Big Data technologies with an adept analysis to obtain as much information as possible from the data and facilitate the decision-making process. Many research areas such as medicine and astrophysics have heavily utilized DS, usually focusing on structured scientific data. Using DS, the scientist can obtain a better understanding of the data and conduct a more precise analysis. In addition, DS has become a crucial foundation for artificial intelligence based on the right mix of machine learning and domain knowledge and continued to impact all aspects of life, through the discovery of new knowledge and hidden meaning within the data.
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