The data life cycle
- Master data management
- Meta data management
- Data integration
- Data Preparation
The data lifecycle is the sequence of steps that a particular data item traverses from its initial generation or capture to archiving and / or eventual deletion at the end of its useful life.
The different stages in the life cycle of master data
Although the specifics vary, Master Data Management experts often identify six or more stages in the data lifecycle. For example:
- Generation or collection: : In this phase, the data enters an organization, usually by data entry, acquisition from an external source, or receipt of a signal, such as transmitted sensor data.
- Servicing: In this phase, the data is processed before use. Data may undergo processes such as integration, clean-up, and extraction-transformation-loading.
- Active use : In this phase, the data is used to support the goals and operations of the organization.
- Publication: In this phase, the data is not necessarily available to the general public, but is simply sent out of the organization. Publication may or may not be part of the life cycle of a particular data unit.
- Archiving: In this phase, data is removed from all active production environments. The data is no longer processed, used or published but stored in case it is needed again in the future.
- Purge: In this phase, each copy of the data is deleted. In general, this operation is performed on already archived data.
Why a life cycle for master data?
Life cycle management of master data is becoming increasingly important since the explosion of big data and the continued development of the Internet of Things (IoT). Huge volumes of data are being generated by an ever increasing number of devices worldwide. Adequate monitoring of data throughout the life cycle is essential for maximizing its utility and minimizing the potential for errors and risks. Finally, archiving or deleting the data at the end of its useful life ensures that it does not consume more resources than necessary.