Information quality: the potential of data and analytics to generate knowledge (Record no. 1732)

MARC details
000 -LEADER
fixed length control field 02652nam a2200229 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250801153438.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250801b2017|||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781118890646
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Kenett, Ron S.
Relator term Author
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Shmueli, Galit
Relator term Co-Author
245 ## - TITLE STATEMENT
Title Information quality: the potential of data and analytics to generate knowledge
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New Jersey:
Name of publisher Wiley Data and Cybersecurity,
Year of publication 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xviii, 363p.
500 ## - GENERAL NOTE
General note Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis<br/><br/>Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management.<br/><br/> This book:<br/><br/>Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain.<br/>Presents a framework for integrating domain knowledge with data analysis.<br/>Provides a combination of both methodological and practical aspects of data analysis.<br/>Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects.<br/>Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys.<br/>Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website.<br/> This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Dimensions of information quality and InfoQ assessment
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term InfoQ at the postdata collection stage
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term InfoQ at the study design stage
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://ieeexplore.ieee.org/servlet/opac?bknumber=9820786
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Books
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