iPhoneAlle anzeigen
iPhone 11iPhone 11 ProiPhone 11 Pro MaxiPhone 12iPhone 12 ProiPhone 12 Pro MaxiPhone 12 miniiPhone 13iPhone 13 ProiPhone 13 Pro MaxiPhone 13 miniiPhone 14iPhone 14 PlusiPhone 14 ProiPhone 14 Pro MaxiPhone 15iPhone 15 PlusiPhone 15 ProiPhone 15 Pro MaxiPhone 16iPhone 16 PlusiPhone 16 ProiPhone 16 Pro MaxiPhone 16eiPhone 8iPhone 8 PlusiPhone SE 2020iPhone SE 2022iPhone XiPhone XRiPhone XSiPhone XS Max
Galaxy A-SerieAlle anzeigen
Galaxy A12Galaxy A13Galaxy A13 5GGalaxy A14Galaxy A15Galaxy A16Galaxy A17Galaxy A17 5GGalaxy A20eGalaxy A21Galaxy A22Galaxy A23Galaxy A24Galaxy A25Galaxy A26 5GGalaxy A32Galaxy A33Galaxy A34Galaxy A35Galaxy A36 5GGalaxy A37Galaxy A40Galaxy A41Galaxy A42Galaxy A50Galaxy A51Galaxy A52Galaxy A53Galaxy A54Galaxy A55Galaxy A56 5GGalaxy A57 5GGalaxy A70Galaxy A71Galaxy A72
Redmi SeriesAlle anzeigen
Redmi 10Redmi 13CRedmi 15 5GRedmi Note 10Redmi Note 10 ProRedmi Note 11Redmi Note 11 ProRedmi Note 11 Pro Plus 5GRedmi Note 11sRedmi Note 12Redmi Note 12 5GRedmi Note 12 ProRedmi Note 12 Pro 5GRedmi Note 12 Pro PlusRedmi Note 13Redmi Note 13 5GRedmi Note 13 ProRedmi Note 13 Pro PlusRedmi Note 14Redmi Note 14 Pro PlusRedmi Note 15Redmi Note 15 5GRedmi Note 15 ProRedmi Note 15 Pro 5GRedmi Note 15 Pro Plus 5GRedmi Note 8Redmi Note 8 ProRedmi Note 9Redmi Note 9 Pro
- Startseite
Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Handbook of Data Quality
Handgeprüfte Gebrauchtware
Bis zu 50 % günstiger als neu
Der Umwelt zuliebe
Optischer Zustand
Beschreibung
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for… individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches. 53,49 €
Taschenbuch | Neu
oder
zzgl.
Du kannst wie immer einen Kaufalarm setzen, wenn du auf das gebrauchte Buch warten möchtest.
zzgl.
Handgeprüfte Gebrauchtware
Bis zu 50 % günstiger als neu
Der Umwelt zuliebe
Technische Daten
Erscheinungsdatum
20.06.2015
Sprache
Englisch
EAN
9783642441844, 9783642441844
Herausgeber
Springer Berlin
Sonderedition
Nein
Seitenanzahl
438
Auflage
1
Einbandart
Taschenbuch
Buch Untertitel
Research and Practice
Autorenporträt
Shazia Sadiq is professor of computer science at the University of Queensland where she teaches and conducts research on information systems with a particular focus on business processes management, governance, risk and compliance, and data quality. Shazia is a keen advocate of cross-disciplinary and industry relevant research, and she has published her results in more than 100 scientific papers so far.
Schlagwörter
data governance, data integration, data provenance, data quality, data warehouses, database management, duplicate detection, entity resolution, information quality, records management
Thema-Inhalt
UN - Datenbanken
UNH - Informationsrückgewinnung, Information Retrieval
UND - Data Warehousing
KJQ - Wirtschaftsmathematik und -informatik, IT-Management
UMB - Algorithmen und Datenstrukturen
GPF - Informationstheorie
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: J.B. Metzler, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
-.-
★★★★★
☆☆☆☆☆ Leider noch keine Bewertungen
Leider noch keine Bewertungen
Sicher bei rebuy kaufen
Schreib die erste Bewertung für dieses Produkt!
Wenn du eine Bewertung für dieses Produkt schreibst, hilfst du allen Kund:innen, die noch überlegen, ob sie das Produkt kaufen wollen. Vielen Dank, dass du mitmachst!
Sicher bei rebuy kaufen