Data integration plays a pivotal role in modern organizations by consolidating data from disparate sources to facilitate analysis, decision-making, and strategic planning. However, the success of data integration initiatives heavily depends on the quality of integrated data. In this paper, we propose a comprehensive data quality framework tailored specifically for the integration process. The framework encompasses strategies for data cleaning, Upholding data consistency and Integrity, Exception Handling Mechanisms, monitoring, documentation, and governance. We present implementation guidelines and discuss the importance of each component in ensuring the reliability, accuracy, and consistency of integrated data. Furthermore, we illustrate the practical application of the framework through case studies in various industries, highlighting its effectiveness in addressing real-world integration challenges.