NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

It's all analytics. (Record no. 5538)

MARC details
000 -LEADER
fixed length control field 06261cam a22005891i 4500
001 - CONTROL NUMBER
control field 9780429343957
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240213122829.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr |||||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210719s2021 nyua ob 001 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 9781000433999
Qualifying information (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000433994
Qualifying information (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000433982
Qualifying information (PDF ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000433986
Qualifying information (PDF ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780429343957
Qualifying information (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0429343957
Qualifying information (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367359713
Qualifying information (hbk.)
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.4324/9780429343957
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1264403995
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1264403995
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q335
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 041000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 071000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 083000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code KJC
Source bicssc
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Burk, Scott William,
Dates associated with a name 1961-
Relator term author.
245 10 - TITLE STATEMENT
Title It's all analytics.
Number of part/section of a work Part II,
Name of part/section of a work Designing an integrated AI, analytics, and data science architecture for your organization /
Statement of responsibility, etc. Scott Burk, David Sweener, Gary Miner.
250 ## - EDITION STATEMENT
Edition statement 1st.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York :
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 :
Other physical details illustrations (black and white)
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
336 ## - CONTENT TYPE
Content type term still image
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note <P>Part 1: Designing for Organizational Success</P><P>Chapter 1: Some Say it Starts with Data, It Doesn't</P><P>Chapter 2: The Anatomy of a Business Decision</P><P>Chapter 3: Trustworthy AI</P><B><P>Part 2: Designing for Data Success</P></B><P>Chapter 4: Data Design for Success</P><P>Chapter 5: Data in Motion, Data Pipes, APIs, Microservices, Streaming, Events and More</P><P>Chapter 6: Data Stores, Warehouses, Big Data, Lakes and Cloud Data</P><P>Chapter 7: Data Virtualization</P><P>Chapter 8: Data Governance and Data Management</P><P>Chapter 9: Miscellanea -- Curated, Purchased, Nascent and Future Data</P><B><P>Part 3: Designing for Analytics Success</P></B><P>Chapter 10: Technology to Create Analytics</P><P>Chapter 11: Technology to Communicate and Act Upon Analytics</P><P>Chapter 12: To Build, Buy, or Outsource Analytics Platform</P>
520 ## - SUMMARY, ETC.
Summary, etc. Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It's All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful. This Book II in the series is divided into three main parts: Part I, Organizational Design for Success, discusses . The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture - the company culture culture!!! To be successful, the CEO's and Decision Makers of a company / organization must be fully cognizant of the cultural focus on establishing a center of excellence in analytics'. Simply, "culture - company culture" is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses .. Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy. Part III, Analytics Technology Design for Success, discusses . Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.
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 Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Decision making.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Visual analytics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Big data.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS / Management
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS / Leadership
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BUSINESS & ECONOMICS / Information Management
Source of heading or term bisacsh
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Sweenor, David,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Miner, Gary,
Relator term author.
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Taylor & Francis
Uniform Resource Identifier <a href="https://www.taylorfrancis.com/books/9780429343957">https://www.taylorfrancis.com/books/9780429343957</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>

No items available.

© 2022- NLU Meghalaya. All Rights Reserved. || Implemented and Customized by
OPAC Visitors

Powered by Koha