The data lifecycle is a way of describing the different stages that data will go through, from collection to dissemination and archival/destruction. The purpose of the data and its lifecycle should be well understood by anyone who handles the data, from its collection to the eventual output.
This section of the framework describes the stages of the data lifecycle in more detail, and outlines quality issues that may occur at each stage.
Quality across the data lifecycle
Quality assessment and assurance should take place at each stage of the lifecycle. The measures used will change at each stage.
Throughout the data lifecycle, those involved should be aware of future users of the data and possible onward uses of the data, and should ensure that data quality at each stage is documented and communicated clearly.
Data practitioners may sometimes need to return to earlier stages in the lifecycle to correct data quality problems.
The stages of the data lifecycle
The data lifecycle illustrated here is not intended to be prescriptive. It is designed to illustrate the journey that data will take through most organisations and identify points at which data quality problems could happen. The actual data lifecycle for an organisation will be specific to the organisation and its processes.
Data leaders may find it helpful to use the data lifecycle here to design one for their own organisation.