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001 978-3-031-71871-7
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020 _a9783031718717
_9978-3-031-71871-7
024 7 _a10.1007/978-3-031-71871-7
_2doi
050 4 _aQA76.9.B45
072 7 _aUN
_2bicssc
072 7 _aCOM021000
_2bisacsh
072 7 _aUN
_2thema
100 1 _aYu, Haiyan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_986784
245 1 0 _aData Quality Management in the Data Age
_h[electronic resource] :
_bExcellence in Data Quality for Enhanced Digital Economic Growth /
_cby Haiyan Yu.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXIX, 90 p. 26 illus., 17 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Service Science,
_x2731-3751
505 0 _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.
520 _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.
650 0 _aBig data.
_957216
650 0 _aBusiness information services.
650 0 _aService industries.
_968307
650 0 _aDatabase management.
_960571
650 0 _aArtificial intelligence
_xData processing.
650 0 _aQuantitative research.
650 1 4 _aBig Data.
_957216
650 2 4 _aIT in Business.
650 2 4 _aServices.
_968308
650 2 4 _aDatabase Management.
_960571
650 2 4 _aData Science.
650 2 4 _aData Analysis and Big Data.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031718700
776 0 8 _iPrinted edition:
_z9783031718724
830 0 _aSpringerBriefs in Service Science,
_x2731-3751
_981892
856 4 0 _uhttps://doi.org/10.1007/978-3-031-71871-7
912 _aZDB-2-BUM
912 _aZDB-2-SXBM
999 _c64580
_d64580