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001 9910900173703321
005 20251202132348.0
010   $a9783031718717
010   $a3031718712
024 7 $a10.1007/978-3-031-71871-7
035   $a(CKB)36431241600041
035   $a(MiAaPQ)EBC31745205
035   $a(Au-PeEL)EBL31745205
035   $a(DE-He213)978-3-031-71871-7
035   $a(EXLCZ)9936431241600041
100   $a20241029d2024      u|         0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aData Quality Management in the Data Age $eExcellence in Data Quality for Enhanced Digital Economic Growth /$fby Haiyan Yu
205   $a1st ed. 2024.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024.
215   $a1 online resource (103 pages)
225 1 $aSpringerBriefs in Service Science,$x2731-3751
311 08$a9783031718700 
311 08$a3031718704 
320   $aIncludes bibliographical references.
327   $aIntroduction of data quality management -- Quality management in Data Science -- Pillars of data quality management -- Tools of data quality management -- Experimental designs for data quality control -- High-quality data collection in data markets -- Ghost data in data quality management -- Summary.
330   $aThis book addresses data quality management for data markets, including foundational quality issues in modern data science. By clarifying the concept of data quality, its impact on real-world applications, and the challenges stemming from poor data quality, it will equip data scientists and engineers with advanced skills in data quality management, with a particular focus on applications within data markets. This will help them create an environment that encourages potential data sellers with high-quality data to join the market, ultimately leading to an improvement in overall data quality. High-quality data, as a novel factor of production, has assumed a pivotal role in driving digital economic development. The acquisition of such data is particularly important for contemporary decision-making models. Data markets facilitate the procurement of high-quality data and thereby enhance the data supply. Consequently, potential data sellers with high-quality data are incentivized to enter the market, an aspect that is particularly relevant in data-scarce domains such as personalized medicine and services. Data scientists have a pivotal role to play in both the intellectual vitality and the practical utility of high-quality data. Moreover, data quality control presents opportunities for data scientists to engage with less structured or ambiguous problems. The book will foster fruitful discussions on the contributions that various scientists and engineers can make to data quality and the further evolution of data markets.
410  0$aSpringerBriefs in Service Science,$x2731-3751
606   $aBig data
606   $aBusiness information services
606   $aService industries
606   $aDatabase management
606   $aArtificial intelligence$xData processing
606   $aQuantitative research
606   $aBig Data
606   $aIT in Business
606   $aServices
606   $aDatabase Management
606   $aData Science
606   $aData Analysis and Big Data
615  0$aBig data.
615  0$aBusiness information services.
615  0$aService industries.
615  0$aDatabase management.
615  0$aArtificial intelligence$xData processing.
615  0$aQuantitative research.
615 14$aBig Data.
615 24$aIT in Business.
615 24$aServices.
615 24$aDatabase Management.
615 24$aData Science.
615 24$aData Analysis and Big Data.
676   $a005.8
700   $aYu$b Haiyan$f1984-$01886675
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910900173703321
996   $aData Quality Management in the Data Age$94522224
997   $aUNINA