Abstract: Governmental regulations have accelerated the development of information technology and resource grouping. One area of "digital gold" that is extremely practical and scientific is large-scale data mining. This is not simply a contemporary issue; it also calls for the rapid expansion of public service. As a result, it is possible to fully realise the advantages of information, improve service effectiveness, and close the service gap. Due to its speedy accounting, low memory requirements, and effective resource allocation, cloud computing has grown in popularity. Big data was therefore used in this work to analyse the current state of public cloud services, and fuzzy evaluation was used to analyse accurate monitoring. Eventually, the structure of the public service was enhanced, and a strategy for the precise organisation of the complete big data-driven public service process was created. According to a fuzzy comprehensive assessment, the design value and data entropy of public cloud services were increasing exponentially; the average design value of the accurate organisation for cloud-based government services was around 4.35, and the average significance of data entropy was around 0.98. Furthermore, big data-driven precision organisation of social public social welfare outperformed traditional precision monitoring of cloud-based services for the public, with results that suggested effects were 7% higher and overall capacity was 9% higher than the compared techniques.
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