Open AccessAnalytic Model and Assessment Framework for Data Quality Evaluation in State Grid
Author(s) -
Zhe Li,
Sai Wu,
Hongwei Zhou,
Sheng Zou,
Ting Dong
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1302/2/022083
Subject(s) - computer science , big data , workflow , data quality , data model (gis) , grid , process (computing) , data modeling , quality (philosophy) , data mining , smart grid , database , systems engineering , data science , engineering , artificial intelligence , operations management , metric (unit) , philosophy , geometry , mathematics , electrical engineering , epistemology , operating system
With the construction of information infrastructure and the smart grid development, big data platform become an important component to support the construction of smart grid, as a consequence, the quality of the data contain in the big data platform become an important part of the process of big data platform construction. In this paper, a discussion about the current data quality analysis model was presented and also the typical data quality problem appears in the process of information infrastructure construction of the State Grid Corporation is analyzed. On the basis of this, the data quality assessment for the information system in the whole life cycle of the State Grid Corporation is designed. As a result, data quality can be checked by the analysis model in order to ensure the data quality level in the whole life cycle of the information system, finally a case was carried out for the preliminary analysis by using the mentioned framework, the result show that this framework can be effective in embedded into the workflow and can be helpful for the data quality assessment.