Data Lifecycle Management (DLM) is a policy-based approach of best practices to oversee the flow of an information system's data through its lifecycle, from creation to deletion. It includes stages such as storage, backup, archiving, and disposal and is employed by organizations that managesensit...
Data lifecycle management (DLM) is an approach to managing data throughout its lifecycle, from data entry to data destruction.
1. What is data lifecycle management (DLM)? Data lifecycle management includes all of the processes, policies and procedures an organization uses to manage business data, from creation through destruction. DLM isn’t a specific product; rather, it’s a framework that ensures a comprehensive approa...
Data Lifecycle Management helps you manage the end-to-end lifecycle of all content across your organization's digital estate, including Microsoft 365, third-party clouds, hybrid deployments, and any content you bring into Microsoft 365. Trainable classification and automated retentio...
Data Lifecycle Management (DLM) helps businesses turn big data from a risky, highly-regulated, critical mass of numbers into a powerful tool to drive growth.
Data Lifecycle Management helps you manage the end-to-end lifecycle of all content across your organization's digital estate, including Microsoft 365, third-party clouds, hybrid deployments, and any content you bring into Microsoft 365. Trainable classification and automated retentio...
The data lifecycle is the sequence of stages data goes through, from creation to disposal, encompassing its entire lifespan within an organization or system.
Given the "lifecycle" of data as the period covering its creation, utilization, storage, and annulment, DLCM is a means of data management that transfers data to the optimum storage at each of these lifecycle stages, thereby reducing total cost of ownership (TCO) while maintaining the optimum...
Data lifecycle management is a set of policies, procedures, and processes that ensure the confidentiality, integrity, and availability of information. A data lifecycle management framework optimizes the value of information and protects it from creation to end-of-life. Data lifecycle management offers...
Data lifecyle management automate the organization of data into separate tiers according to specified policies. Another source of confusion is the difference between DLM and information lifecycle management (ILM). Although they're sometimes used interchangeably, they differ in important ways. According to...