Research on Optimization Method of Enterprise Financial and Accounting Information Quality Based on Big Data Analysis

Financial and accounting information needs to reflect the economic activities and financial status of the enterprise fully and completely. However, in practice, due to the delay, omission or error of information transmission, the integrity and consistency of financial and accounting information may be damaged, resulting in greater difficulty in data quality optimization. Therefore, this study proposes a method of optimizing the quality of enterprise financial and accounting information based on big data analysis. Based on big data, a feedforward accounting data cleaning model is constructed to filter out the accounting information with disturbing factors. Based on chaos algorithm, the abnormal information is detected by clustering fusion technology, and the information quality is optimized. The experimental results show that: The research method can detect abnormal financial and accounting information with high precision and low communication cost.