Data Science: Domains, Process, Roles and Responsibilities

Abstract

The study of information retrieval and analysis, or data science, tries to identify information and correspondence hidden in raw, defined information. To extract useful information from data, data science therefore combines programming expertise with understanding of mathematics and statistics.  In the field of data science, machine learning algorithms are employed to handle various types of input, including numerical, textual, visual, and auditory data. Therefore, algorithms perform certain tasks related to data extraction, cleaning, and processing and in turn produce data that becomes a real value for any organization. Fraud detection, targeted marketing, healthcare diagnostics, proactive treatment, and recommendation systems are a few examples of data science applications. Big data's expansion and the accessibility of effective computing resources have made data science more and more relevant in recent years. Because of this, data science has become a field in high demand, and there is a growing need for experts in the sector. Because data now gives businesses a competitive edge, we often talk about data science, but what does that mean? In this study, we have tried to go deeper into this subject.