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Current conventional multi-source heterogeneous data governance methods mainly judge data attributes to achieve sub-regional data cleaning, which leads to poor governance performance due to the lack of analysis of non-linear data. In this regard, a multi-source heterogeneous data governance technique based on cloud data center is proposed. The ETL function in the relational database is adopted to clean the data, and the data transformation mode as well as the data cleaning rules are defined. Mutual information coefficient is introduced to determine the degree of data relevance, and nonlinear data relevance analysis is performed. The cloud data center is used as a carrier to construct the multi-source heterogeneous data governance system. In the experiments, the governance performance of the proposed data governance technique is examined. The final test results show that the proposed data governance technique has a high checking accuracy rate and a more ideal data governance effect.