In attempt to define what data lifecycle, data management professionals describe data lifecycle as phases with each having unique features. This phases include;
- Data capturing where data values were not available before. This phase is further subdivided into; i) data acquisition ii) data entry iii) signal reception
- Data maintenance includes tasks such as data movement, cleansing, integration and enrichment
- Data synthesis involves creation of data values by use of inductive reasoning and other input methods.
- Data usage is where data is applied in the management of an organization or business enterprise.
- Data publication which involves sharing information with other business units or enterprises.
- Data archival occurs when data is copied to external environment in case it is needed in the near future.
As a matter of facts, some data processes or phase it is not a must that they follow every step discussed in the above phases.
The way data is managed is very important to an organization, institution or any other unit of administration should be the best way ever due to the following reasons;
- Retrieving and understanding it when the need prompts.
Some organizations happens to have a lot of information to handle and therefore, the method used to manage data should permit ease retrieval.
- Saving time.
Without an efficient data management system, all manually undertaken task would take a lot of time to have them completed. An organization therefore should adopt the best method from a range of alternatives so as to save time.
For example, an organization with many employees should a method which guarantees maximum privacy to its data. This is because some data is very sensitive to be left in the hands of the public. These include passwords, income and tax for the organization among others.
The cost of getting the exact data after it has been misplaced, data failure or loss is very high. Thus, an organization should maximize on the type of data management tool which can have a backup in case of data lose.
The cost of incorrect data and the process of correcting the same data may sum up to millions which may see the organization coming stand still in its operation.
The reputation and the public image displayed by the same mistakes may affect the production, distribution and marketing process and hence low revenue.
- Ensure research integrity
Research is one of the projects which needs high levels of ethics and therefore, the possible method to be adopted should comply with the stipulated research ethics.
- Be able to meet funding agency requirements
Some data management programs as well as tools are relatively expensive and this may be very important to any donor agency. Proper data handling gives an overview or the organization and therefore if an organization doesn’t hold an efficient methods of data management will risk itself from getting donor funding.
- Prevent duplication of information
A well designed data management tool should be free from unwanted duplication of information for this may cost the organization its privacy among others cost.