Advances in data science and analytics :  concepts and paradigms / 
edited by M. Niranjanamurthy, Hemant Kumar Gianey and Amir H. Gandomi. 
 - 1 online resource (xvi, 331 pages) :  illustrations (some color) 
<br/><br/>Includes bibliographical references and index. 
<br/><br/> Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, deep learning, and big data. Data analytics software is a more focused version of this and can even be considered part of the larger process. Analytics is devoted to realizing actionable insights that can be applied immediately based on existing queries. For the purposes of this volume, data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. While a data scientist is expected to forecast the future based on past patterns, data analysts extract meaningful insights from various data sources. Although data mining and other related areas have been around for a few decades, data science and analytics are still quickly evolving, and the processes and technologies change, almost on a day-to-day basis. This volume provides an overview of some of the most important advances in these areas today, including practical coverage of the daily applications. 
<br/><br/><label>ISBN: </label>9781119792819 1119792819 9781119792826 1119792827 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Data mining.<br/>Big data.<br/>Exploration de donn�ees (Informatique)<br/>Donn�ees volumineuses.<br/>Big data<br/>Data mining
<br/><br/><label>LC Class. No.: </label>QA76.9.D343  / A38 2023 
<br/><br/><label>Dewey Class. No.: </label>006.312