[AG.DLM.5] Reduce risks and costs with systematic data retention strategies

Category: FOUNDATIONAL

Data is continuously generated, processed, and stored throughout the development lifecycle, increasing the complexity and importance of automated data management capabilities. Automated data retention and disposal is the process of implementing strategies and tools that systematically store data for pre-established periods and securely delete it afterward. The goal of data retention and disposal is not just about compliance, but also about reducing risks, sustainability, minimizing costs, and improving operational efficiency. Automation reduces the manual workload, decreases the risk of human error, and improves data governance and compliance.

To effectively implement automated data retention and disposal, start by defining the data lifecycle policies for your organization. This includes understanding the regulatory and business requirements for each type of data your organization processes, how long it needs to be retained, and the conditions under which it should be disposed. The policies should also include procedures for data archiving, backups, and restoration.

Once these policies are in place, automate the enforcement of these policies with data lifecycle management tools. These tools can automatically handle tasks like deletion, archival, or movement of data based on the predefined rules. As part of the automation process, develop mechanisms to log and audit data disposal actions. This not only provides accountability and traceability but also is essential for demonstrating compliance during audits.

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