In today’s data-driven world, businesses are drowning in information. Extracting value from this information overload can be an intricate process. In this blog, we will explore the different stages of a data life cycle in an organization.
Stages of Data Life Cycle
1. Data Generation:
At first phase, it involves generating data in different forms including documents, images, databases and more. Some common approaches used for acquisition of data include capture, entry and external sources acquisition.
2. Data Storage:
It is crucial to store data that will be useful in future times. While cloud-based storage is a mode of modern practice, traditional methods comprise physical storage devices and servers for instance USB, hard drive, and CDs.
3. Data Usage:
During this stage, data becomes a strategic resource that helps in organizational objectives. It can also be shared internally or externally after being presented with facts such as which gender prefers what kind of clothing.
4. Data Archiving:
To guarantee both compliance with regulations and availability of information organizations have separate storage environments where they keep inactive valuable data in archives hence this can be reinstated at any one time when needed.
5. Data Destruction:
There is need for effective management as volumes increase on daily basis mainly due to costs associated with storing them coupled with regulatory requirements making it essential for organizations to have protocols on how obsolete ones are destroyed securely
The importance of understanding data lifecycle
Today, every firm knows that data is valuable, and it must be handled with great caution. Data lifecycle management is vital for effective data governance in an organization. Such information enables you create ideas on a project or an initiative within the company.
