5 Phases of Data Life Cycle

The General Reference
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The data life cycle is the full process that data goes through in its lifetime, beginning at its creation and ending with its destruction.

Following the data lifecycle can have large benefits to an organisation allowing them to manage and streamline their data to better suit their needs. It can also improve the security of the data and ensure it follows the regulations and laws in place.

5 phases of data lifecycle

The 5 phases of the data lifecycle are:

  1. data creation
  2. data storage
  3. data usage
  4. data archiving
  5. data destruction

1: Data Creation

The generation or capture of data. This can happen through a variety of processes such as through sensors, human input or surveying. Data can also be obtained secondarily through websites, apps or third-party collectors.
Data collection can come in three forms: 
  • Data Acquisition: collating third-party data that already exists
  • Data Entry: collection of primary data from within an organisation
  • Data Capture: collection of data from devices, such as sensors, from within an organisation

2: Data Storage

As soon as data is collected it must be stored in a secure, protected environment. This stage can also involve the transformation or processing of data to ensure it is ready for analysis.
The location of storage depends on the type of data being collected, as well as the size of the organisation collecting it. Backups and recovery protocols should also be initialised here to further secure the data.

3: Data Usage

At this stage, data use analysed and further processed to extract the useful and most comprehensive data. Once the good quality data is extracted, it can be used to make choices. For more information on what makes good quality data, see 2.3 - Information Quality. Conclusions that have been drawn from this data can also be shared to third-parties or other relevant people or organisations at this stage. 

4: Data Archiving

When data can no-longer be used or has fulfilled its purpose, it can be archived. This involves the duplication of data to a storage environment where it can be used again should it be needed. When data is archived, it does not require maintenance due to its lack of use. However, it should still be easily accessible in the event of a situation in which the data is useful again.

5: Data Destruction

If data is no longer needed and organisations can be sure it will not be useful in the future, it should be safely destroyed. This reduces the chance of sensitive information being passed on to bad actors. It also ensures organisations comply with data protection regulations. For more information on how data can be disposed of safely, see 5.6 - Safe Disposal of Data. Data can be disposed of digitally or physically. This choice depends on the type and sensitivity of the data in question.

Summary of the 5 Stages of Data Lifecycle

Data Creation: The generation or capture of data
Data Storage: The storage and processing of data in a secure environment
Data Usage: The analysis and extraction of information from data
Data Archiving: The storage of data that is currently not needed
Data Destruction: The safe disposal of sensitive data that will never be needed again

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