data life cycle

1. Determine the need. Before generating new data or capturing existing data, ensure that the need for such data is established and confirmed.
2. Generation or capture. In this phase, data comes into an organization, usually through data entry, acquisition from an external source or signal reception, such as transmitted sensor data.
3. Data preparation for use. In this phase, data is processed to prepare it to be used. The data might be subjected to processes such as integration, scrubbing and extract, transform, and load (ETL). It might also be encrypted to ensure its security and privacy.
4. Active use. In this phase, data is used to support the organization's objectives and operations.
5. Management. During the management phase, data might be made available to the broader public or retained inside the organization. It can be stored in a short-term storage platform for continued availability while its security and privacy is constantly maintained.
6. Long-term storage, retention or archiving. In this phase, data is removed from all active production environments and moved to an archive. It is no longer processed, used or published, but it is stored in case it is needed again in the future. The data might be stored on hard disk drives (HDDs), solid-state drives (SSDs) or tape in-house or with a cloud storage service.
7. Purging and destruction. When the data becomes obsolete, every copy of data is deleted and destroyed as part of a removal process. The data might have been archived or it is data that is no longer needed or has been superseded by newer data. The data destruction process might also include the media on which the data resides.