DATA SCIENCE AND DATA ANALYTICS : (Record no. 72146)

000 -LEADER
fixed length control field 03842cam a2200493Ki 4500
001 - CONTROL NUMBER
control field 9781003111290
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711212801.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211007s2021 xx ob 0|1 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781003111290
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1003111297
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000423198
-- (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000423190
-- (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000423228
-- (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000423220
-- (electronic bk. : EPUB)
082 04 - CLASSIFICATION NUMBER
Call Number 005.7
245 00 - TITLE STATEMENT
Title DATA SCIENCE AND DATA ANALYTICS :
Sub Title opportunities and challenges.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (1 volume) :
520 ## - SUMMARY, ETC.
Summary, etc Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy. FEATURES Gives the concept of data science, tools, and algorithms that exist for many useful applications Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems Identifies many areas and uses of data science in the smart era Applies data science to agriculture, healthcare, graph mining, education, security, etc. Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm's productivity.
700 1# - AUTHOR 2
Author 2 Tyagi, Amit Kumar,
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.taylorfrancis.com/books/9781003111290
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- [Place of publication not identified] :
-- CHAPMAN & HALL CRC,
-- 2021.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
588 ## -
-- OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big data.
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- COMPUTERS / Database Management / Data Mining
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- COMPUTERS / Database Management / General

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