Assessing Value Data Quality by Mair Gregor (8 results)

Condition: New. pp. 60.

Taschenbuch. Condition: Neu. Assessing the Value of Data Quality | A Normative Approach | Gregor Maximilian Mair | Taschenbuch | 60 S. | Englisch | 2014 | AV Akademikerverlag | EAN 9783639454086 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the recent decades data collection and data harvesting were established as useful tools to improve production and sales, to satisfy customers, etc. With vast amounts of data stored and processed the topic of data quality gained importance. Empirical studies show that maintaining good data quality is imperative to fully utilize the potential of data. Today, data management projects schedule huge budgets on data maintenance. Yet, the value of improving data quality remains obscure and intangible. But how can high investments on data maintenance be justified This work proposes a definition and a normative model to assess the value of data quality according to this definition. Approaches to calculate the normative value of data are adopted to develop a model fully based on theory of probabilities and statistical decision theory. By applying the model to different scenarios the behaviour of the value of data quality, as proposed in this work, is studied in an axiomatic manner. By analysing the results of these studies consequences of bad data quality are illustrated and discussed. Finally, a formal way to assess and rank data quality improvement measures is demonstrated. 60 pp. Englisch.…

Condition: New. Print on Demand pp. 60 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 60.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the recent decades data collection and data harvesting were established as useful tools to improve production and sales, to satisfy customers, etc. With vast amounts of data stored and processed the topic of data quality gained importance. Empirical studies show that maintaining good data quality is imperative to fully utilize the potential of data. Today, data management projects schedule huge budgets on data maintenance. Yet, the value of improving data quality remains obscure and intangible. But how can high investments on data maintenance be justified This work proposes a definition and a normative model to assess the value of data quality according to this definition. Approaches to calculate the normative value of data are adopted to develop a model fully based on theory of probabilities and statistical decision theory. By applying the model to different scenarios the behaviour of the value of data quality, as proposed in this work, is studied in an axiomatic manner. By analysing the results of these studies consequences of bad data quality are illustrated and discussed. Finally, a formal way to assess and rank data quality improvement measures is demonstrated.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mair Gregor MaximilianDI (FH) in Software Engineering at the Upper Austria Polytechnic University of Hagenberg. Technical student at CERN, Geneva. Research assistant at the Astro- and Particle Physics Institute the University of Inns.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In the recent decades data collection and data harvesting were established as useful tools to improve production and sales, to satisfy customers, etc. With vast amounts of data stored and processed the topic of data quality gained importance. Empirical studies show that maintaining good data quality is imperative to fully utilize the potential of data. Today, data management projects schedule huge budgets on data maintenance. Yet, the value of improving data quality remains obscure and intangible. But how can high investments on data maintenance be justified This work proposes a definition and a normative model to assess the value of data quality according to this definition. Approaches to calculate the normative value of data are adopted to develop a model fully based on theory of probabilities and statistical decision theory. By applying the model to different scenarios the behaviour of the value of data quality, as proposed in this work, is studied in an axiomatic manner. By analysing the results of these studies consequences of bad data quality are illustrated and discussed. Finally, a formal way to assess and rank data quality improvement measures is demonstrated.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.…