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Harnessing Automation for Effective SaaS Data Management and Compliance


As organizations grapple with the challenge of managing vast amounts of unmanaged data across Software-as-a-Service (SaaS) systems, there has been a significant shift toward automation for efficient information governance -- which has increasingly directed IT staff's focus toward information governance and compliance issues.


A revealing report by DoControl, titled "Quantifying the Immense Risk of Unmanaged SaaS Data Access," for example, highlights that 40% of all SaaS assets remain unmanaged, leading to a substantial rise in inappropriate internal, external, and public access to sensitive data. This widespread data sprawl not only increases the risk of data leaks but also intensifies insider and external threats to global organizations.


Often, these risks are exacerbated by multiple SaaS applications that integrate poorly and lack proper management, leading to sensitive corporate data proliferating into unintended locations.

The problem is further compounded by the finding that an average 1,000-person company might store between 500,000 to 10 million assets in SaaS applications, with as many as 200,000 of these assets potentially being shared publicly. This situation underscores an urgent need for robust information governance and security measures and highlights the crucial role of automation in aligning security settings with business objectives.


Automating information governance processes is proven to not only boost efficiency and reduce costs but also enhance data quality. For example, Xerox has successfully implemented automated data categorization systems that improve data organization and retrieval, thereby enhancing operational efficiency. Moreover, automation aids organizations in complying with various stringent regulations such as the General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA), and the Sarbanes-Oxley Act (SOX), as well as numerous retention laws.


Effective automation of data processing and retention has been shown to consistently meet these standards and reduce the risk of adverse data events and is crucial for cost-effectively integrating new technologies such as cloud computing, big data, and artificial intelligence into organizational processes.


The result is that IT teams are tasked with developing information governance-centric automated systems that ensure organizational information is managed in a compliant and secure manner. An example of such innovation includes using robotic process automation to perform compliance checks within a data governance framework, ensuring all financial records adhere to international banking regulations.


This strategic pivot towards IG automation does not merely mitigate risks; it significantly enhances the efficiency and reliability of compliance programs, demonstrating the indispensable role automation plays in modern data governance strategies. 




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