Abstract
After years accumulation of informationization construction, power enterprises have established huge and complex application systems, which include multi-class data related to business like production, operation and management. Along with the demands of developing new business application, the data integration is urgently needed to grasp overall data view; however the complex data integration environment causes the data quality problem particularly outstanding. Under the background of the power industry, this paper first studies the data quality definition and dimension recognition; then proposes a data integration platform architecture and studies the data quality control methods in data integration; elaborates data quality assessment methods and procedures; in the view of data product, designs a total data quality management (TDQM) process finally. In a typical case of application, the results show the practicability of the proposed method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chanana V, Koronios A (2007) Data quality through business rules. In: International conference on information and communication technology (ICICT 2007). IEEE Press, Dhaka, pp 262–265
Chen Shuyong, Song Shufang, LI Lanxin, Shen Jie (2009) Survey on smart grid technology. Power Syst Technol 33(1–7)
Dillard RA (1992) Using data quality measures in decision-making algorithms. IEEE Expert 7:63–72
Karr AF, Sanil AP, Banks DL (2006) Data quality: a statistical perspective. Stat Methodol 3:137–173
Liufei (2008) The white paper of data integration and data quality market in Chinese enterprises. IDC Company
Michnik J, Lob MC (2009) The assessment of the information quality with the aid of multiple criteria analysis. Eur J Oper Res 195:850–856
Pipino LL, Lee YW, Wang RY (2002) Data quality assessment. Commun ACM 45:211–218
Redman TC (2005) Measure data accuracy: a framework and review. Infor Qual Adv Manag Info Syst 1:21–36
Songmin, Tanzheng (2007) Reviews of foreign studies on data quality management. J Inf 2:7–9
Wang RY (1998) A product perspective total data quality management. Commun ACM 41:58–65
Wang RY, Strong DM (1996) Beyond accuracy: what data quality mean to data consumers. J Manag Inf Syst 12:5–33
Wang RY, Storey VC, Firth CP (1995a) A framework for analysis of data quality research. IEEE Trans Knowl Data Eng 7:623–640
Wang RY, Reddy MP, Kon HB (1995b) Toward quality data: an attribute-based approach. Decis Support Syst 13:349–372
Yang Qingyun, Zhao Peiying, Yang Dongqing, Tang Shiwei, Tong Yunhai (2004) Research on data quality assessment methodology. Comput Eng Appl 9:3–5
Zhang Liang (2009) Research on data quality for electric power dispatch data centers. East China Electr Power 37:403–405
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, K., Duan, C., Zhu, Y. (2013). The Research of Data Quality Problems in Power Enterprise Data Integration. In: Xu, B. (eds) 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34910-2_31
Download citation
DOI: https://doi.org/10.1007/978-3-642-34910-2_31
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34909-6
Online ISBN: 978-3-642-34910-2
eBook Packages: Business and EconomicsBusiness and Management (R0)