By IT Brew Staff
less than 3 min read
Definition:
A step-by-step process for managing data from its creation all the way to its deletion, data life-cycle management has five main phases:
- Data creation: In the first stage of the life-cycle, data is created or captured from various sources (e.g., mobile applications, manual entry, web forms, etc.). At this stage, it’s important to establish metadata tagging to help classify different pieces of data and implement processes for standardization.
- Data storage: After data enters your ecosystem, it needs to be stored. How you store that data will vary; some of it may be stored in the cloud, while others may be kept in a relational database or on an on-prem solution.
- Data usage and sharing: Once stored, data is ready to be used within an organization. At this stage, companies should sort and classify stored data, as well as establish who within the company can access it.
- Data archival: Data that is no longer needed on a daily basis may be archived for recordkeeping and compliance purposes. As part of this stage, data is moved to a long-term storage option like magnetic tape or a cloud storage-as-a-service provider. How long data is archived for will depend on a company’s specific DLM strategy.
- Data deletion: The life-cycle ends with data deletion. In this stage, data is disposed of in a secure manner to provide space for new data or to comply with regulation. Companies may physically destroy storage mediums containing data or otherwise permanently delete the data.
Why DLM exists
DLM is important for several reasons. For one, some companies may need to follow regulatory requirements, like the Health Insurance Portability and Accountability Act (HIPAA), that require them to delete data after a certain amount of time. A good DLM strategy can also enhance data quality and accuracy while helping save costs, as businesses won’t need to devote resources to storing unnecessary data.
