NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

Common Data Sense for Professionals : (Record no. 5939)

MARC details
000 -LEADER
fixed length control field 04460cam a2200553Ki 4500
001 - CONTROL NUMBER
control field 9781003165279
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240213122832.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu|||unuuu
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211007s2021 xx fo 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency OCoLC-P
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency OCoLC-P
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003165279
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1003165273
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000514117
Qualifying information (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000514110
Qualifying information (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367760502
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000514100
Qualifying information (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000514102
Qualifying information (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367760489
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1273728005
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1273728005
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number T58.6
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 043060
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 063000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 041000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code KJMV3
Source bicssc
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 658.4038
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Jugulum, Rajesh.
245 10 - TITLE STATEMENT
Title Common Data Sense for Professionals :
Remainder of title A Process-Oriented Approach for Data-Science Projects.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture [Place of publication not identified] :
Name of producer, publisher, distributor, manufacturer Productivity Press,
Date of production, publication, distribution, manufacture, or copyright notice 2021.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xviii, 100 pages).
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Foreword Preface AcknowledgementsOverviewChapter 1: The Meeting of Manju and JimChapter 2: Understanding the ProblemChapter 3: Analyzing the Problem and Collecting DataChapter 4: Creating and Analyzing ModelsChapter 5: Project StructureChapter 6: Data Science Stories and Case Example AnalysisChapter 7: Concept ReviewChapter 8: Manju and Jim's Concluding MeetingReferences
520 ## - SUMMARY, ETC.
Summary, etc. Data is an intrinsic part of our daily lives. Everything we do is a data point. Many of these data points are recorded with the intent to help us lead more efficient lives. We have apps that track our workouts, sleep, food intake, and personal finance. We use the data to make changes to our lives based on goals we have set for ourselves. Businesses use vast collections to determine strategy and marketing. Data scientists take data, analyze it and create models to help solve problems. You may have heard of companies having data management teams, or Chief Information Officers (CIO) or Chief Analytics Officers (CAO), etc. These are all people that work with data, but their function is more related to vetting data and preparing it for use by data scientists. The jump from personal data usage for self-betterment to mass data analysis for business process improvement often feels bigger to us than it is. In turn, we often think big data analysis requires tools held only by advanced degree holders. Though an advanced degrees are certainly valuable, this book illustrates how it is not a requirement to adequately run a data science project. Because we are all already data users, with some simple strategies and exposure to basic statistical analysis software programs, anyone who has the proper tools and determination can solve data science problems. The process presented in this book will help empower individuals to work on and solve data- related challenges. The goal for this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study -- it illustrates how the various topics discussed can be applied. Essentially, this book helps traditional business people to solve data related problems on their own without any hesitation or fear. The powerful methods are presented in the form of conversations, examples, and case studies. The conversational style is engaging and provides clarity.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Business
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Decision making
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Big data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Business intelligence.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS / Marketing / Research
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS / Strategic Planning
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS / Management
Source of heading or term bisacsh
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Taylor & Francis
Uniform Resource Identifier <a href="https://www.taylorfrancis.com/books/9781003165279">https://www.taylorfrancis.com/books/9781003165279</a>
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified OCLC metadata license agreement
Uniform Resource Identifier <a href="http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf">http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf</a>

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