Handbook of Data Quality Research and Practice /
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...
| Published in: | Springer eBooks |
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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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| Online Access: | http://dx.doi.org/10.1007/978-3-642-36257-6 Перейти в каталог НБ ТГУ |
Table of Contents:
- Research and Practice in Data Quality Management
- Data Quality Management Past, Present, and Future: Towards a Management System for Data
- Data Quality Projects and Programs
- On the Evolution of Data Governance in Firms: The Case of Johnson & Johnson Consumer Products North America
- Cost and Value Management for Data Quality
- Data Warehouse Quality: Summary and Outlook
- Using Semantic Web Technologies for Data Quality Management
- Data Glitches: Monsters in your Data
- Generic and Declarative Approaches to Data Quality Management
- Linking Records in Complex Context
- A Practical Guide to Entity Resolution with OYSTER
- Managing Quality of Probabilistic Databases
- Data Fusion: Resolving Conflicts from Multiple Sources
- Ensuring the Quality of Health Information: The Canadian Experience
- Shell's Global Data Quality Journey
- Creating an Information Centric Organisation Culture at SBI General Insurance
- Epilogue: The Data Quality Profession.