Secure and Scalable AI-Powered Data Governance Models for Salesforce Cloud-Based Enterprises
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I2P120Keywords:
Artificial Intelligence, Data Governance, Salesforce, Cloud Computing, Compliance Automation, Machine Learning, Cybersecurity, Blockchain, Enterprise SystemsAbstract
Enterprise data management practices have been reshaped by the fast uptake of cloud-based Customer Relationship Management (CRM) systems especially Salesforce. Though cloud environment is scalable, flexible and cost efficient, it also brings in great problems with data governance, privacy, compliance, and security. The growing size, rate and types of the enterprise data prompt the need to establish intelligent and automated systems of governance that are capable of guaranteeing regulatory compliance, data integrity, and lessening risks. Artificial Intelligence (AI) is a potential solution to help overcome these issues by implementing predictive analytics, detecting anomalies, automated classification, and implementing policies. In this paper, I will present an effective and secure data governance framework on Salesforce understanding cloud-based businesses based on AI. The model suggested will combine machine learning, deep learning, and rule based compliance engines to automate the data classification, access control, and risk assessment, audit management. The framework uses metadata analytics, natural language processing, and behavioral profiling to promote the effectiveness of governance. Also, audit trail and encryption are added features based on blockchain to guarantee transparency and information integrity. The research paper gives an extensive literature review on the available models of governance and their weaknesses. A comprehensive methodology is formulated which includes data preparation, model learning, deployment structure, and metrics of evaluation. The experimental outcomes illustrate an increase in compliance levels, decrease in governance delays and availability of extra security stability in comparison with conventional strategies. The results validate the hypothesis that AI-enhanced governance is ultra-efficient and that the Salesforce ecosystems respond to regulatory compliance. The suggested framework offers businesses with a dynamic, adaptable, and forward-thinking governance framework that can handle the changing regulatory and security demands. The study will be of value to the current efforts to develop intelligent cloud governance systems, as well as provide useful insights to implement those systems in the enterprise.
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