Data integration is a problem of combining data residing at different sources and providing the user with a unified view of these data. An important issue in data integration is the possibility of conflicts among the different data sources. Data sources may conflict with each other at data value level which is defined as data inconsistency. So in this paper, a solution for data inconsistency in data integration is proposed. An approximate object-oriented data model extended with data source quality criteria is defined. On the basis of our data model, we provide a data inconsistency solution strategy. To accomplish our strategy, fuzzy multi-attribute decision making approach based on data source quality criteria is applied to select the "best" data source's data as the data inconsistency solution. A set of experiments is designed and performed to evaluate the effectiveness of our strategy and algorithm. The experimental results indicate that our solution performs ideally.