LEADER 03480nam 22004813 450 001 9910900173703321 005 20241102060311.0 010 $a9783031718717 010 $a3031718712 035 $a(CKB)36431241600041 035 $a(MiAaPQ)EBC31745205 035 $a(Au-PeEL)EBL31745205 035 $a(Exl-AI)31745205 035 $a(EXLCZ)9936431241600041 100 $a20241102d2024 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Quality Management in the Data Age $eExcellence in Data Quality for Enhanced Digital Economic Growth 205 $a1st ed. 210 1$aCham :$cSpringer,$d2024. 210 4$d©2024. 215 $a1 online resource (103 pages) 225 1 $aSpringerBriefs in Service Science Series 311 08$a9783031718700 311 08$a3031718704 327 $aPreface -- Background and Significance -- Acknowledgments -- Contents -- About the Author -- List of Figures -- List of Tables -- Chapter 1: Introduction of Data Quality Management -- 1.1 Introduction -- 1.1.1 Data Quality Issues -- 1.1.2 Concepts of Data Quality -- 1.1.3 Structure of This Book -- 1.2 Brief Overview of Data Quality Management -- 1.3 Development of Data Quality Management -- 1.3.1 Deming and Quality Management -- 1.3.2 Progress of Quality Management -- 1.4 Concept of Data Quality Management -- 1.4.1 Definition of Data Quality -- 1.4.2 Components of Data Quality Control -- 1.5 Impact of Data Quality in Data Markets -- 1.5.1 Impact of DQ on AI Performance -- 1.5.2 Impact of DQ on Treatment Effects Identification -- 1.5.3 Impact of DQ on Data Exchange and Transaction -- References -- Chapter 2: Quality Management in Data Science -- 2.1 The Evolution of Quality Management -- 2.1.1 Development of Statistics -- 2.1.2 Evolution from Probability to Data Computation -- 2.1.3 Data Is Power -- 2.1.4 Divide and Conquer$7Generated by AI. 330 $aHaiyan Yu's book, 'Data Quality Management in the Data Age,' focuses on the critical role of high-quality data in driving digital economic growth. It explores the necessity of data markets to procure high-quality data and the challenges of managing data quality, particularly in data-scarce fields like personalized medicine. The book outlines the dimensions and metrics of data quality, the impact of low-quality data, and presents theories on quality management in data science. It is tailored for data scientists, engineers, data market managers, researchers, and graduate students in quality engineering and service science. By enhancing data quality management skills, the book aims to improve the data market environment, encouraging the participation of data sellers with high-quality data. It also discusses recent advancements in statistical quality control methods and offers a case study on data quality management.$7Generated by AI. 410 0$aSpringerBriefs in Service Science Series 606 $aData editing$7Generated by AI 606 $aKnowledge economy$7Generated by AI 615 0$aData editing. 615 0$aKnowledge economy. 700 $aYu$b Haiyan$01767740 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910900173703321 996 $aData Quality Management in the Data Age$94214050 997 $aUNINA