Research on unstructured data processing technology in executing audit based on big data budget

Abstract

The wave of big data has promoted the transformation of auditing technology, which has brought about tremendous changes to auditing models and auditing methods. The traditional audit data analysis methods cannot analyze semi-structured and unstructured data, nor can they meet the requirements of the development of audit informatization in the context of big data. New ideas and methods for audit data analysis are urgently needed. In this context, the article proposes an audit data analysis framework based on text mining, and describes the detailed audit data analysis process of collecting and storing, mining and analysing, summarizing and publishing. By using text mining technology to mine the unstructured original audit data collected, different text mining models are established according to the clear audit requirements, the audit data is analysed, and then audit doubts are found, and ultimately formable audit evidence and audit trail. The construction of the framework aims to provide new ideas for big data audits to reduce the risk of big data audits and improve audit quality.