With the rapid development of Internet of things and big data，the amount of data collected by the supervisory control and data acquisition (SCADA) system is growing exponentially, resulting in that the traditional swing door trending (SDT) algorithm can no longer meet the needs of the SCADA system for historical data compression. We propose an advanced swing door trending (ASDT) algorithm and implement it in Java language based on the deep research on the data compression method and the SDT algorithm particularly. The ASDT algorithm which uses sine curve fitting data to achieve data compression has better compression results in comparison with the traditional SDT algorithm. Experimental results show that compared with the traditional SDT algorithm，the ASDT algorithm can improve the compression ratio without significant increase in compression error.