An Integration Model of Multi-Source Heterogeneous Audit Data

Abstract

This paper shows the problem of multi-source heterogeneous data integration in the audit data storage and access problems. Based on the analyses of existing data integration model, combining with the service-oriented architecture theory, this paper proposes a data center pattern, which is suitable for multi-source heterogeneous data integration model to audit. Furthermore this paper puts forward an incremental based technology to show the problem of synchronization of business audit data integration model, and expounds the data management mode based on Middleware technology.

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“…Artificial intelligence, ML, and cloud computing will be helpful for BD Analysts. Moreover, Li, Chai, and Chen [46] summarized that the heterogeneous data in industry are produced easily but are difficult to store, manage, and audit. In this study, the issue of heterogeneity of large firms was solved using a NoSQL-based data integration model.…”

“…Domain Contributions [43] Oil and Gas High performance measure [44] Agriculture High performance, high availability, and high scalability, using the latest techniques [45] General-Purpose Data generation, storing, fetching, analysis, visualization, and decision-making [46] Banking Helps in auditing the multisource data [47] Healthcare Facilitate for navigation of HL7 FHIR core resources [48] General-Purpose Delivering automatic services to interoperable system [49] Healthcare Helps in developing an automatic system for disordered patient [50] Education To motivate researchers and academicians about the latest techniques [10] Healthcare Useful for decisions of scientific, clinical, and administrative work [51] Education Facilitate in online learning, storage, processing, and academic activities [52] General-Purpose Recommendation system, opinion mining, and parallelism can be targeted [53] Oil and Gas Helpful for decision-makers during exploration, drilling, and production [54] General-Purpose It will facilitate for fetching data and performance measure [65] Healthcare Helpful for disease prevention, tracking, and policy making [11] Healthcare Helps in boosting statistical power of sustainable and robust data [55] Infrastructure Geographic based smart city for aggregation, visualization, and analysis [56] Healthcare Helps in predicting the clinical codes of patient stays…”