Recently, big data is considered a critical strategic resource by many countries and regions. However, difficult data circulation and insufficient data regulation commonly exist in the big data era, thereby leading to the serious phenomenon of data silos, poor data quality, and difficulty in unleashing the potential of data elements. This provokes researchers to explore data integration techniques for breaking data barriers, enabling data sharing, improving data quality, and activating the potential of data elements. Relational data and knowledge graphs, as two significant forms of data organization and storage, have been widely applied in real life. To this end, this study focuses on relational data and knowledge graphs to summarize and analyze the key technologies of data integration, including entity resolution, data fusion, and data cleaning. Finally, it prospects future research directions.