00893nam0-22002891i-450-99000089691040332120001010000089691FED01000089691(Aleph)000089691FED0100008969120001010d--------km-y0itay50------baitay-------001yyStructural Engineering Seminar "Change to the Building Code" A Preview of the 1994 UBC.Los AngelesSEAOSCDInamica, SismicaStructural Engineers Association of Southern California492472UbcITUNINARICAUNIMARCBK99000089691040332103 D.0,139Dip.327IINTCIINTCStructural Engineering Seminar "Change to the Building Code" A Preview of the 1994 UBC357119UNINAING0103480nam 22004813 450 991090017370332120241102060311.097830317187173031718712(CKB)36431241600041(MiAaPQ)EBC31745205(Au-PeEL)EBL31745205(Exl-AI)31745205(EXLCZ)993643124160004120241102d2024 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierData Quality Management in the Data Age Excellence in Data Quality for Enhanced Digital Economic Growth1st ed.Cham :Springer,2024.©2024.1 online resource (103 pages)SpringerBriefs in Service Science Series9783031718700 3031718704 Preface -- 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 ConquerGenerated by AI.Haiyan 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.Generated by AI.SpringerBriefs in Service Science SeriesData editingGenerated by AIKnowledge economyGenerated by AIData editing.Knowledge economy.Yu Haiyan1767740MiAaPQMiAaPQMiAaPQBOOK9910900173703321Data Quality Management in the Data Age4214050UNINA