methodology

Data Lifecycle Management

Data Lifecycle Management (DLM) is a comprehensive approach to managing the flow of data from its creation or acquisition through to its archival or deletion. It involves policies, processes, and tools to ensure data is handled efficiently, securely, and in compliance with regulations throughout its entire lifespan. This methodology typically includes stages such as creation, storage, usage, sharing, archiving, and destruction.

Also known as: DLM, Data Lifecycle, Information Lifecycle Management, ILM, Data Management Lifecycle
🧊Why learn Data Lifecycle Management?

Developers should learn and implement Data Lifecycle Management when building systems that handle sensitive, regulated, or large-scale data, such as in healthcare, finance, or e-commerce applications. It helps ensure data quality, reduce storage costs, maintain compliance with laws like GDPR or HIPAA, and mitigate risks associated with data breaches or loss. Use cases include automating data retention policies, optimizing database performance, and managing data backups and recovery.

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