The Data Life Cycle describes the stages that your organisation goes through. From the initial capture to the decisions ultimately made through its use.
Organisations that manage their data life cycle are far more likely to benefit from Data Analytics and even AI.
There are many views on the life cycle of data, and each has its own context.
My perspective on the Data Life Cycle is to use data for the betterment of an organisation through supporting strategic decision makers.
Capturing data from every part of your organisation within a range of software systems.
Data is captured manually or automatically.
It takes the form of customer orders, staff timesheets, operational data, live feeds from connected technology, and so on.
Most data is automatically categorised within the system its captured in. Categorisation provides a context to the data and gives it meaning beyond the software system.
This is what allows us to match up customer orders in one system with customer sales calls in another.
Data maintenance involves cleansing and enriching the data already captured and updating it to reflect changes in the real world.
Again, a great deal of that is automated.
Maintaining data incurs an enormous amount of manual work due to the adhoc nature of it.
Data is the backbone of all reporting within an organisation, and Every report relies on the previous stages happening correctly.
Correcting errors found in the prior phase requires a huge amount of manual work.
Business Intelligence is gaining traction, and we are finding more organisations extending their traditional reports with dashboards.
As a result, dashboards are live and interactive, as well as connected to the data already.
The C-Suite and executives need to be well informed about the performance of their organisation so they can make the most appropriate decision.
Some Data Life Cycles include disposal as the final stage.
I’d argue that you shouldn’t delete or archive anything, and you don’t need to.
It costs almost nothing to store petabytes of data, so why not keep it.
You never know when it may be useful.