Organizations handle data lifecycle management (DLM) by implementing structured processes that manage data from its creation to its deletion. This involves several key stages: data creation, storage, usage, archiving, and deletion. By outlining these stages, organizations ensure that data is handled in a way that meets regulatory requirements, security standards, and business needs. For instance, a company may establish policies that dictate how customer data is collected and stored, ensuring that it is only kept as long as necessary and that access is restricted to authorized personnel.
Data storage is typically managed through reliable databases and cloud services, where organizations often categorize data based on its importance and access frequency. For example, frequently accessed data might be stored in high-performance databases for rapid access, while less critical data could be moved to slower, more cost-effective storage solutions. During the usage phase, organizations focus on data analysis and processing, utilizing tools that facilitate data insights while adhering to data governance policies. They may also implement logging and monitoring systems to track who accesses data and how it is used, ensuring compliance and protecting sensitive information.
When it comes to archiving and deletion, organizations establish retention policies that specify how long data should be kept and when it should be securely deleted. For example, financial organizations often retain transaction records for a specific number of years due to legal requirements, after which the data can be anonymized or securely erased. This systematic approach not only helps in minimizing storage costs but also reduces the risk of data breaches and ensures that organizations comply with legal obligations, thereby maintaining their credibility and trust with customers.